Predicting the function of a protein form either a sequence or a structure (is not trivial) Adam Godzik The Sanford-Burnham Medical Research Institute

Summary - overview Homology based methods Analogy based methods Physics based methods Why function prediction?

What we mean by function Multilevel definition Phenotype Cellular function Molecular function (activity) Substrates Inhibitors cofactors Several attempts to develop a unified function classification EC classification for enzymes Merops (proteases), CAZY (hydrolases) Gene ontology

Two, complementary views of the evolution and diversity of life Organisms (species)Genes (proteins)

Both are amazingly large and diverse Organisms (species) About 1.5M known today, million species estimated to exists, depending on the definition of species and other assumptions Their relations can be described in a tree of life, at least for eukaryotes. Bacterial and archeal tree of life is much more controversial, some even dispute the concepts of species for bacteria Proteins With 20 amino acid alphabet, the number of possible protein sequences is very large ( i.e. 1.2* short proteins(!)) Total number: >10billions? M species, with ~4K genes in a bacterial and ~10K in an eukaryotic genome Over 25 million known today, i.e. ~0.2% Representative sample?

From the 25 million proteins known today Direct experimental data is available for few thousand proteins Indirect experimental data are available for perhaps few hundred thousand Structures of ~60 thousands have been solved

protein universe seems to be very large. But is it random?

Many proteins (like species) are close relatives Histone H1 (human) - histone H1 (chicken) SRRSASHPTYSEMIAAAIRAEKSRGGSSRQSIQKYIKSHYKVGHNADLQIKLSIRRLLAA | | || || || ||| ||| | |||||||||||||||||| ||| |||||| || SKKSTDHPKYSDMIVAAIQAEKNRAGSSRQSIQKYIKSHYKVGENADSQIKLSIKRLVTT similarity: 77% id, BLAST e.value 0.0 function: two H1 histones from different species (orthologs) Their functions and structures are obviously very similar

We can organize the protein universe into neighborhoods (families)?

Number of protein clusters (modeling families) grows linearly in number of protein sequences (and exponentially in time) – cumulative total From Yooseph et al, PloS Biology, (2007) 5:e16 How many protein families are still out there?

How far can we go? Histone H5 - histone H1 TYSEMIAAAIRAEKSRGGSSRQSIQKYIKSHYKVGHNADLQIKLSIRRLLAAGVLKQTKGVGASGSFRLA | | | | | | | | | ||| | | | |||| |||||||| SVTELITKAVSASKERKGLSLAALKKALAAGGYDVEKNNSRIKLGLKSLVSKGTLVQTKGTGASGSFRLS similarity: 40% seq id, BLAST e.value function: two histones (paralogs) Structures still very similar, functions somewhat different, but obviously similar

This is surely too far? Histone H5 - TRANSCRIPTION FACTOR E2F-4 PTYSEMIAAAIRAEKSRGGSSRQSIQKYIKSHYKVGHNADLQIKLSIRRLLAAGVLKQTKGVGASGSFRL | | | | | GLLTTKFVSLLQEAKD-GVLDLKLAADTLA------VRQKRRIYDITNVLEGIGLIEKKS----KNSIQW similarity :7% seq id, BLAST e.value 1

Is it?  Structure – obviously similar (2.4 Å RMSD over 80 aa)  function – clearly related (both bind DNA)  More subtle similarity can be detected with more sophisticated methods

We can keep adding more layers

most “ function assignments ” are provided by predicted homology Unknown protein GLLTTKFVSLLQEAKDGVLDLKL AADTLAVRQKRRIYDITNVLEGIG LIEKKSKNSIQW Well studied protein SRRSASHPTYSEMIAAAIRAEKS RGGSSRQSIQKYIKSHYKVGHN ADLQIKLSIRRLLAA Similarity -> homology prediction ? similarity

Similarity -> homology based annotations Recognition of close and/or distant homologs based on similarity Sequence Sequence/profile, profile/profile Structure Problems How to predict differences? Even homologous proteins evolve and change!

Prediction by homology Recognition Are there any well characterized proteins similar to my protein? Can we assume they are homologous? Structure of my protein is similar to the other one Modeling Alignment What is the position-by-position target/template equivalence Function prediction Function of my protein is similar to the other one

We could predict activity Role in the whole organism 3D structure Structure of a complex

Important distinction Similarity Two proteins have similar sequences/structures/function s if by some metric the s/s/f of one protein is more similar to the s/s/f of another than to a randomly chosen protein Homology Two proteins are homologous if they have evolved from a common ancestor Common error Two proteins are 65% homologous What we really meant The sequences of two proteins are 65% similar, therefore we can safely assume they are homologous, why else they would be so similar?

If life would be easy, this is how it would look like similar homologous not similar unrelated

Not (obviously) similar, but (probably) homologous Histon H5 and transcription factor E2F4, identity 7%, similar fold, similar function (DNA binding) PTYSEMIAAAIRAEKSRGGSSRQSIQKYIKSHYKVGHNADLQIKLSIRRLLAAGVLKQTKGVGASGSFRL | | | | | GLLTTKFVSLLQEAKD-GVLDLKLAADTLA------VRQKRRIYDITNVLEGIGLIEKKS----KNSIQW

Similar, but not homologous phosphoribosyltransferase and viral coat protein, identity: 42%, different folds, different functions IRLKSYCNDQSTGDIKVIGGDDLSTLTGKNVLIVEDIIDTGKTMQTLLSLVRQY.NPKMVKVASLLVKRTPRSVGY 173 : ||. ||| || |. || | : | | | | || | || |:| | ||.| | 214 VPLKTDANDQ.IGDSLY....SAMTVDDFGVLAVRVVNDHNPTKVT..SKVRIYMKPKHVRV...WCPRPPRAVPY 279

Similarity vs. homology similar homologous not similar unrelated not similar homologous similar not homologous

Can we return to this simple picture by redefining similarity? similar homologous not similar unrelated

Are these two protein families related? New protein (target) KAAELEMEKEQILRSLGEISVHNCMFKLEECDREEI EAITDRLTKRTKTVQVVVETPRNEEQKKALEDATLM IDEVGEMMHSNIEKAKLCLQ Known protein (template) VKKDALENLRVYLCEKIIAERHFDHLRAKKILSREDTEEISCRTS SRKRAGKLLDYLQENPKGLDTLVESIRREKTQNF

How to compare two families? Score = ?

Compare as vectors in 21 dimensional space (FFAS) Profile-profile similarity

How to validate a protocol 1. Recognition Folding benchmarks from structural clustering of PDB (several sets, 700 pairs used here)compared to sequence based clustering of the same group of proteins correct predictions vs. wrong predictions CASP meetings, CAFASP, LiveBench published and/or publicly available predictions, fold prediction servers, available prediction programs

Summary - overview Homology based methods Analogy based methods Physics based methods Why function prediction?

Similarity -> analogy based annotations Recognition of potential analogs based on similarity in Genome organization (non homologous replacements) Genomic fingerprints Expression patterns Specific features Charge distribution Presence of specific patterns Problems Is this similarity related to function?

TM0449 (thy1) – from prediction to proof TM0449 Hypothetical, uncharacterized protein Multiple homologs in pathogenic and thermophilic bacteria Novel fold evidence Phylogenetic profile complementing thymidylate synthase A homolog complements TS in Dictyostelium Confirmed experimentally

3D motif search finds an identical arrangement binding phosphate in a different protein

Summary - overview Homology based methods Analogy based methods Physics based methods Why function prediction?

“ Ab initio function prediction ” – substrate docking

We know the structure of one protein in the family and functions of some others – is the function conserved? Newly solved target Gallery of models

We can analyze conservation of surface features by mapping them on the sphere

And then compare maps between homologs

And come up with new (predicted) functions Phospholipid vs. retinol vs. short peptide binding

Summary - overview Homology based methods Analogy based methods Physics based methods Why function prediction?

Why my interest in function prediction? Structural genomics: the structure is often the easiest experimental information to obtain (after sequence)

Function vs function We witnessed dramatic technological advances in sequencing and now structure determination, function analysis remain a painstaking, manual effort. We used to know a lot about function even before we started working on a protein. Well, not anymore ? 1 year Structure determination 1970 Function discovery Sequencing

purificationexpression cloning struc. refinement struc. validation annotation publication phasing data collection xtal screening tracing bl xtal mounting crystallizationimaging harvesting target selection 3 X 2 X 5 X 1 X 2 X 1 X 2 X 1 X 7 X 1 X PDB 1 X Structure determination is now done on an assembly line

purificationexpression cloning struc. refinement struc. validation annotation publication phasing data collection xtal screening tracing bl xtal mounting crystallizationimaging harvesting target selection 3 X 2 X 5 X 1 X 2 X 1 X 2 X 1 X 7 X 1 X PDB 1 X Even few years ago functional annotation seemed trivial

purificationexpression cloning struc. refinement struc. validation annotation publication phasing data collection xtal screening tracing bl xtal mounting crystallizationimaging harvesting target selection 1 X 2 X 1 X 7 X 1 X PDB 1 X After few years, the reality seems to be very different

“reverse order” of function and structure determination and it’s challenges The classical way 1. A function is discovered and studied 2. The gene responsible in this function is identified 3. Function is confirmed 4. Product of this gene is isolated, crystallized solved. 5. we have a whole story! Structure “rationalizes” function and provides molecular details Post-genomic 1. a new, uncharacterized gene is found in a genome 2. predictions or high-throughput methods prioritize this gene for further studies 3. the protein is studied in detail Structure is solved in a high throughput center Structure is the first experimental information about the “hypothetical” protein

We now have hundreds of structures of proteins with unknown functions

Summary For some, function prediction is a practical, day to day problem Analogy based approaches dominate the field Homology seen from sequence similarity structural similarities Potential active sites, clefts, surface features Many useful tools exists, but they are very scattered and not very user-friendly

Summary (2) Avoid overconfidence - “easy” predictions contain many surprises Only synergy of several independent lines of reasoning can give a correct answer Elimination of “easy”, but inconsistent predictions is critical So far, AFP doesn’t even come close to expert analysis