BY DEVELOPING
THE FIRST
CELL FREE SYSTEM
TO SUPPORT A VERTEBRATE CHROMOSOME.
DNA REPLICATION USING FROG EGG EXTRACTS.
AND THIS WORK TRANSFORMED
THE STUDY OF DNA REPLICATION.
IN 1999, DOCTOR WALTER JOINED HARVARD
MEDICAL SCHOOL AS AN ASSISTANT PROFESSOR
AND WAS LATER
PROMOTED TO FULL PROFESSOR IN 2010.
AND SINCE 2013, HE HAS ALSO BEEN
AN INVESTIGATOR AT THE HARVARD
HUGHES MEDICAL INSTITUTE
AND DOCTOR WALTER REMAIN
AS A DEDICATED EDUCATOR,
TEACHING DNA REPLICATION
AND REPAIR IN GRADUATE
GRADUATE COURSES AT HARVARD.
WE'RE THRILLED TO HAVE HIM HERE TODAY
TO SHARE.
HIS INSIGHTS AND EXPERTISE
FOR THE AUDIENCE.
SO PLEASE
PUT ANY QUESTIONS IN THE CHAT BOX
AND WE WILL GO THROUGH THEM
AT THE END OF THE SEMINAR.
AND PLEASE JOIN ME IN WELCOMING
DOCTOR JOHANNES. WATER.
WELL, THANK YOU VERY MUCH, CHUN,
FOR THE VERY NICE INTRODUCTION.
CAN EVERYONE HEAR ME?
YES WE CAN.
OKAY, GREAT.
SO. YEAH.
SO IT'S A REAL PLEASURE AND HONOR
TO BE ABLE TO GIVE THIS TALK IN
WHAT I GUESS IS THE ORIGINAL,
GENOME MAINTENANCE WEBINAR.
AND, I'M VERY EXCITED TO TELL YOU TODAY
ABOUT HOW WE HAVE TACKLED
A REALLY CLASSIC PROBLEM,
THE PROBLEM OF HOW TRANSCRIPTION
IS COUPLED TO REPAIR
USING A FEW NEW APPROACHES.
ONE OF THESE IS A CELL FREE SYSTEM
THAT WE HAVE DEVELOPED THAT SUPPORTS TC-NER
AND ANOTHER IS USING
AN IN SILICO SCREENING
METHOD
TO LOOK FOR NEW PROTEIN
PROTEIN INTERACTIONS.
AND BY COMBINING THESE APPROACHES,
WE THINK WE'VE MADE,
AN IMPORTANT NEW OBSERVATION,
WHICH IS REALLY,
IDENTIFYING THE ROLE OF A PROTEIN CALLED
STK19 AND COUPLING,
TRANSCRIPTION STALLING TO THE DOWNSTREAM
REPAIR EVENTS.
SO I'M GOING TO
BEGIN JUST WITH THE 30,000FT VIEW,
WHICH IS TO SAY THAT COLLECTIVELY,
AS A FIELD,
WE ARE ALL TRYING TO UNDERSTAND,
THE HIGHLY VARIED DNA REPAIR PATHWAYS
THAT RESPOND TO AND FIX THE VERY DIVERSE
LESIONS THAT ARE GENERATED BY EXOGENOUS
AND ENDOGENOUS AGENTS.
AND WE'RE ALSO, OF COURSE,
TRYING TO UNDERSTAND
HOW DEFECTS IN THESE PATHWAYS
GIVE RISE TO THE VARIOUS DISEASES
THAT WE SEE IN HUMANS,
NOT ONLY, TO UNDERSTAND REALLY
THE THE BASIS
OF THESE PATHOLOGICAL STATES, BUT ALSO,
IN SOME CASES TO ACTUALLY SEE
IF WE CAN FIND
SOME, SOME THERAPEUTIC INTERVENTIONS
TO, TO AMELIORATE
SOME OF THESE CONDITIONS.
NOW, MY LABORATORY FOR MANY YEARS
HAS FOCUSED
ON REPLICATION
COUPLED REPAIR OF VERY COMPLEX
LESIONS LIKE DNA INTERSTRAND
CROSS LINKS AND DNA PROTEIN CROSS LINKS.
AND THAT INTEREST CONTINUES.
BUT WHAT I'M GOING TO FOCUS ON
TODAY IS A RELATIVELY NEW INTEREST
IN THE MECHANISM
OF NUCLEOTIDE
EXCISION REPAIR, IN PARTICULAR,
THE TRANSCRIPTION
COUPLED BRANCH OF THIS PATHWAY.
SO LET ME BEGIN
BY GIVING YOU A LITTLE BIT OF
BACKGROUND ABOUT WHAT WE KNOW
ABOUT NUCLEOTIDE EXCISION REPAIR.
THIS IS A PATHWAY THAT REALLY SPECIALIZES
IN THE REPAIR OF VERY BULKY
DNA LESIONS THAT DISTORT THE DNA DUPLEX.
THESE CAN BE GENERATED
BY UV LIGHT, CIGARETTE SMOKE,
AND ALSO VARIOUS ENDOGENOUS ALDEHYDES
AND THESE AGENTS
LEAD TO THE FORMATION
OF THESE BULKY ADDUCT
THAT HAVE THE PROPERTY
OF ACTUALLY DISTORTING THE DNA DUPLEX.
AND IN ONE BRANCH OF NUCLEOTIDE EXCISION
REPAIR, CALLED THE GLOBAL
GENOMIC PATHWAY,
WHICH CAN
IN PRINCIPLE FUNCTION
ANYWHERE IN THE GENOME.
THE DISTORTION IN THE DNA DUPLEX
IS RECOGNIZED BY A PROTEIN CALLED XPC
XERODERMA PIGMENTOSUM
GROUP
C PROTEIN
THAT IS, THAT IS MUTATED IN THIS,
SKIN CANCER PREDISPOSITION SYNDROME.
AND WHAT IT DOES IS REALLY QUITE CLEVER.
IT ACTUALLY SENSES NOT THE LESION ITSELF,
BUT THE DISTORTION IN THE DUPLEX.
AND IT ACTUALLY GRABS
HOLD OF THE NON-DAMAGED STRAND
BY VIRTUE OF THE DESTABILIZATION
OF THE DUPLEX
THAT OCCURS AS A RESULT OF THE DAMAGE.
AND XPC THEN FUNCTIONS TO RECRUIT
THE GENERAL TRANSCRIPTION FACTOR TFIIH
WHICH
WHICH HAS A KEY ROLE
IN INITIATING TRANSCRIPTION.
SO IT ACTUALLY PROMOTES
THE PROMOTER
OPENING AT AT TRANSCRIPTION START SITES.
AND IT HAS A PARTIALLY OVERLAPPING
FUNCTION IN REPAIR.
SO AFTER BEING RECRUITED BY XPC,
THE XPB SUBUNIT OF TFIIH
THIS IS A TRANSLOCASE.
IT'S AN ATPASE
IS THAT TRANSLOCATES ALONG DNA
AND IT ACTUALLY PUMPS
THE DUPLEX TOWARDS THE XPC PROTEIN.
AND IN DOING SO,
IT ROTATES AND UNDERWINDS
THE DNA THAT LEADS
TO LOCAL STRAND SEPARATION.
AND NOW A SECOND
SUBUNIT IN TFIIH, CALLED XPD,
WHICH IS A FIVE PRIME
TO THREE PRIME HELICASE,
GRABS HOLD OF ONE STRAND
AND THEN STARTS TRANS
LOCATING TOWARDS THE SITE OF THE DAMAGE,
AND IF DAMAGE IS PRESENT,
THEN XPD GETS STUCK.
AND THIS IS A PROCESS THAT IS CALLED
LESION VERIFICATION
OR DAMAGE VERIFICATION.
AND THE STALLING OF XPD
THEN NUCLEATES THE DOWNSTREAM EVENTS,
WHICH INCLUDES
THE RECRUITMENT OF STRUCTURE
SPECIFIC ENDONUCLEASES XPF
AND XPG
THAT INCIZE THE DAMAGED STRAND AND,
REMOVE A SHORT OLIGONUCLEOTIDE
CONTAINING THE LESION.
AND THEN THE FINAL EVENT
IS A GAP FILLING STEP.
SO THIS IS THE SO-CALLED GLOBAL
GENOMIC PATHWAY,
WHICH, AS I SAID,
CAN FUNCTION,
ESSENTIALLY ANYWHERE IN THE GENOME.
BUT THERE'S A SECOND
VERY IMPORTANT BRANCH
OF NUCLEOTIDE EXCISION
REPAIR CALLED TRANSCRIPTION
COUPLED REPAIR.
AND THIS COMES INTO PLAY WHEN THE GLOBAL
GENOMIC PATHWAY FAILS TO REMOVE A LESION
AND AN RNA
POLYMERASE COLLIDES WITH THE DAMAGE.
NOW, THIS WOULD BE A TRULY DIRE SITUATION
BECAUSE,
THE LESION STALLS THE POLYMERASE
AND LOCALLY DISRUPTS,
GENE EXPRESSION ON THE ONE HAND
AND ON THE OTHER HAND, THE THE POLYMERASE
ACTUALLY SHIELDS THE LESION
FROM THE GLOBAL GENOMIC PATHWAY.
SO THIS WOULD BE,
REALLY CATASTROPHIC
IF NOT
FOR THE FACT
THAT THE STALLED RNA POLYMERASE ITSELF,
LIKE XPC,
CAN ACTUALLY FUNCTION
AS A SENSOR FOR THE REPAIR PATHWAY.
AND THIS WAS THE INSIGHT OF PHIL HANAWALT
IN THE MID 1980S.
AND SO, WE NOW KNOW
FROM THE WORK
OF MANY PEOPLE IN THE FIELD,
THE SORT OF OUTLINES OF THIS TC-NER
THIS TRANSCRIPTION
COUPLED NUCLEOTIDE EXCISION
REPAIR PATHWAY.
AND REALLY THE FIRST EVENT HERE
IS THE RECRUITMENT
OF AN ATPASE CALLED CSB.
AND THIS PROTEIN IS MUTATED IN
ANOTHER HUMAN DISORDER
CALLED COCKAYNE SYNDROME,
WHICH IS CHARACTERIZED BY,
NEURODEGENERATION AND PROGERIA.
AND WHAT CSB DOES
IS IT ACTUALLY PUSHES ON THE BACK
END OF RNA POLYMERASE
AND TRIES TO MOVE IT PAST OBSTACLES.
AND IF THAT FAILS, AS IN THE CASE OF
VERY BULKY DNA LESIONS, CSB
THEN NUCLEATES THE FORMATION OF A LARGE
SO-CALLED TC-NER COMPLEX.
AND SO THE NEXT PROTEIN TO LOAD IN
THIS SEQUENCE IS AN E3
UBIQUITIN LIGASE CALLED CRL4CSA,
WHOSE KEY
RECOGNITION SUBUNIT IS CALLED CSA.
AND THAT'S ANOTHER ONE OF THE PROTEINS
MUTATED IN THE COCKAYNE SYNDROME.
AND CRL4
DOES A FEW THINGS,
ONE OF WHICH IS THAT IT ACTUALLY
UBIQUITYLATES
RNA POLYMERASE ON A SINGLE RESIDUE.
AND THAT UBIQUITINATION
EVENT IS CRUCIAL FOR REPAIR.
ALTHOUGH WE DON'T REALLY UNDERSTAND
THE MECHANISTIC BASIS FOR THAT.
ANOTHER THING THAT THIS E3 LIGASE DOES
IS TOGETHER WITH CSB, IT
RECRUITS ADDITIONAL FACTORS,
INCLUDING THE GIVES UVSSA PROTEIN
TO COMPLETE THE FORMATION
OF THIS SO-CALLED TC-NER COMPLEX.
AND I'M GOING TO DENOTE IT HERE.
I'M NOT GOING TO,
CONTINUALLY DRAW THE ENTIRE E3 LIGASE.
AND WE ACTUALLY HAVE
A PRETTY GOOD UNDERSTANDING
STRUCTURALLY OF WHAT
THIS TC-NER COMPLEX LOOKS LIKE,
LOOKS LIKE BASED ON BEAUTIFUL WORK
FROM PATRICK KRAMER'S LABORATORY.
AND REALLY, THE FUNCTION OF THIS COMPLEX,
ULTIMATELY, IS TO RECRUIT
THE TFIIH PROTEIN.
AND AS WE SAW IN GLOBAL GENOMIC REPAIR
AND TRANSCRIPTION COUPLED REPAIR,
WHAT IT DOES IS IT LOCALLY OPENS THE DNA.
THAT'S THE FUNCTION AGAIN OF XPB.
AND THAT ALLOWS XPD
TO ENGAGE WITH THE TRANSCRIBED STRAND
AND XPD THEN TRANSLOCATE TOWARDS
THE STALLED POLYMERASE
LOOKING FOR DAMAGE.
AND AGAIN,
IF DAMAGE IS SENSED,
THE WHOLE TFIIH
COMPLEX STALLS AND RECRUITS
THE NUCLEASES
THAT THEN
EXCISED THE LESION AND ALLOW GAP FILLING.
A SECOND POSSIBLE FUNCTION OF THIS XPD
DEPENDENT TRANSLOCATION IS THAT,
IT PROBABLY.
ALTHOUGH THIS HAS NEVER BEEN
DIRECTLY OBSERVED, IT
PROBABLY BACKTRACKS RNA POLYMERASE
TO EXPOSE THE LESION
AND EFFECTIVELY ALLOW
THE DOWNSTREAM EVENTS.
SO YOU CAN REALLY THINK OF,
BOTH OF THESE PATHWAYS,
BOTH BRANCHES,
AS OCCURRING IN THREE BASIC STEPS.
THE SENSING MECHANISM,
WHICH IN THE CASE OF,
GLOBAL GENOMIC REPAIR
REALLY RELIES ON XPC
AND IN THE CASE
OF TRANSCRIPTION COUPLED REPAIR,
REALLY RELIES ON RNA POLYMERASE.
THEN THE VERIFICATION STEP,
WHICH IS COMMON
BETWEEN THE TWO AND DEPENDS ON TFIIH.
AND THEN FINALLY ALSO
THE COMMON
EXCISION AND GAP FILLING EVENTS.
SO, I HOPE THIS GIVES YOU,
A PICTURE
ABOUT WHERE WE ARE IN THE FIELD,
BUT I WOULD LIKE TO POINT OUT
THAT THERE ARE
LOTS OF UNANSWERED
QUESTIONS,
PARTICULARLY ON THE TRANSCRIPTION COUPLED
REPAIR SIDE.
AND THAT'S BECAUSE THIS PATHWAY,
UNLIKE THE GLOBAL GENOMIC PATHWAY,
HAS NOT BEEN FULLY RECONSTITUTED,
WITH PURIFIED COMPONENTS.
AND IN FACT, THERE IS NO CELL FREE SYSTEM
CURRENTLY, AT LEAST UNTIL,
RECENTLY THAT SUPPORTS THIS PATHWAY.
AND SO AS A RESULT,
THERE ARE REALLY SOME
FUNDAMENTAL QUESTIONS
THAT REMAIN UNANSWERED.
ONE OF THOSE IS HOW IS TFIIH
ACTUALLY PROPERLY POSITIONED?
REMEMBER THAT
IN ORDER FOR PRODUCTIVE REPAIR
TO OCCUR, TFIIH
HAS TO BIND DOWNSTREAM OF THE STALLED
RNA POLYMERASE,
AND IT HAS TO SPECIFICALLY ENGAGE
THROUGH XPD WITH THE TRANSCRIBED STRAND.
THAT'S REALLY
THE ONLY CONFIGURATION
THAT WILL LEAD TO A
PRODUCTIVE REPAIR OUTCOME.
AND HOW
TFIIH IS POSITIONED IN THAT
MANNER IS NOT UNDERSTOOD.
FURTHERMORE, WE REALLY UNDERSTAND
LITTLE ABOUT THE
DYNAMICES OF, OF RNA POLYMERASE.
SO, IN THE COURSE OF REPAIR, IS IT,
IS IT BACKTRACKED
AND DOES IT RESTART OR IS IT REMOVED?
THESE ARE SOME UNANSWERED QUESTIONS.
AND ALSO
WHAT IS THE ROLE OF RNA
POLYMERASE UBIQUITINATION.
AND FINALLY,
GIVEN THAT THE PROCESS
HAS NOT BEEN RECONSTITUTED
TO PURIFIED COMPONENTS,
ARE WE ACTUALLY MISSING ANY KEY FACTORS.
AND MIGHT SUCH FACTORS SHED
LIGHT ON ON THE ABOVE QUESTIONS?
SO TODAY I'M GOING TO TELL YOU
ABOUT THE WORK OF A REALLY,
REALLY TALENTED,
POSTDOCTORAL FELLOW,
TYCHO MEVISSEN,
WHO ACTUALLY IS ON THE JOB MARKET.
AND WHAT TYCHO DID WAS TO SAY,
LET'S TRY TO ACTUALLY DEVELOP
A CELL-FREE SYSTEM
THAT SUPPORTS EUKARYOTIC TC-NER.
THERE HAVE BEEN SEVERAL ATTEMPTS
OVER THE YEARS TO ACHIEVE THIS,
AND, UNFORTUNATELY,
NONE OF THEM
HAVE BEEN SUCCESSFUL IN AND
AND THAT'S ACTUALLY PRETTY CLEAR
FROM THE FACT
THAT NONE OF THE CELL-FREE SYSTEMS
THAT HAVE BEEN,
PROPOSED OR DOCUMENTED
ACTUALLY REALLY DEPEND ON THE CORE
TC-NER
FACTORS SUCH AS CSB AND CRL4CSA.
SO TYCHO REASONED THAT
PERHAPS GIVEN
THE EXTRAORDINARY POWER
OF XENOPUS EGG EXTRACTS, TO RECAPITULATE
SO MANY GENOME MAINTENANCE PATHWAYS
INCLUDING CHROMATIN ASSEMBLY,
CHECKPOINT SIGNALING,
REPLICATION AND ALL OF THESE REPAIR
PATHWAYS, MIGHT
IT ALSO BE ABLE TO SUPPORT TC-NER?
THAT WAS REALLY,
THE SORT OF THE OVERARCHING RATIONALE
OF HIS PROJECT.
THERE WAS ONLY ONE SMALL DETAIL,
AND THAT IS THAT FROG
EGG EXTRACTS, AT LEAST CONVENTIONAL
EGG EXTRACTS, WERE KNOWN TO BE INACTIVE
FOR TRANSCRIPTION.
SO THE FIRST THING THAT TYCHO
HAD TO DO TO TRY TO ACTIVATE TC-NER IN
THIS SYSTEM WAS TO ACTIVATE
TRANSCRIPTION ITSELF.
AND THE WAY HE WENT ABOUT DOING
THIS WAS TO GENERATE A PLASMID
THAT CONTAINS, A VERY STRONG.
SOMEHOW MY,
MY MOUSE IS NOT RESPONDING PROPERLY.
HERE. HOLD ON ONE SECOND. LET'S SEE.
MAYBE THERE'S SOME JUNK ON MY.
I'M, INTERESTING.
HOLD ON ONE SECOND.
OKAY.
THIS IS FASCINATING.
MY MOUSE DECIDED TO STOP WORKING.
OKAY.
WELL, SO,
HE USED A PLASMID,
CONTAINING A VERY STRONG CORE PROMOTER
AS WELL AS A FEW UPSTREAM
ACTIVATING SEQUENCES.
AND HE ADDED THIS INTO EGG
EXTRACT TOGETHER
WITH A POTENT TRANSCRIPTIONAL ACTIVATOR
GAL4VP64.
AND INSTEAD OF USING CONVENTIONAL TOTAL
EGG LYSATES,
WHICH OTHERS HAD TRIED BEFORE AND REALLY
DIDN'T LEAD TO ANY SIGNIFICANT
TRANSCRIPTIONAL ACTIVATION,
WHAT HE DID
INSTEAD WAS TO USE A CONCENTRATED
NUCLEARPLASMIC
EXTRACT THAT IS HIGHLY ENRICHED
IN NUCLEAR PROTEINS,
INCLUDING RNA POLYMERASE, MEDIATOR,
AND ALL OF THESE THINGS
THAT THAT ARE NEEDED
TO ACTIVATE TRANSCRIPTION.
AND WHEN HE DID THIS
AND ALSO INCLUDED RADIOACTIVE UTP,
HE SAW A VERY POTENT TRANSCRIPTION.
SO THIS WAS GREAT.
AND, AND MEANT THAT HE HAD OVERCOME
THE FIRST HURDLE TOWARDS
RECAPITULATING TC-NER.
AND I SHOULD NOTE THAT ACTUALLY,
MY FORMER POSTDOC, DAVID LONG,
WHO HAS HIS OWN LABORATORY
IN SOUTH CAROLINA,
ALSO HAS ACTIVATED
TRANSCRIPTION IN FROG EGG EXTRACTS.
ALTHOUGH,
HIS APPROACH INVOLVES THE
USE OF ENDOGENOUS PROMOTERS.
SO, THE GOAL HERE,
OF COURSE, WAS TO RECAPITULATE TC-NER.
SO THE NEXT THING THAT TYCHO DID
WAS TO ENGINEER A CLASSIC NUCLEOTIDE
EXCISION REPAIR SUBSTRATE, A 1,3-GTG
INTRASTRAND
CROSSLINK INTO THE TEMPLATE STRAND.
AND AS YOU CAN SEE FROM THE GEL
OVER ON THE RIGHT,
THIS LED TO VERY POTENT
TRANSCRIPTIONAL ARREST.
AND SO NOW THE QUESTION BECAME
WHETHER ANY OF THESE LESIONS
ARE REPAIRED
IN A TRANSCRIPTION COUPLED MANNER.
EXCUSE ME.
AND TO ADDRESS THIS,
TYCHO USED A SIMPLE TRICK
WHICH WAS TO ASK
WHETHER A PML1 RESTRICTION SITE
THAT COINCIDES
WITH THE LESION IS REGENERATED.
SO THE INPUT PLASMID CANNOT BE CUT
WITH THIS ENZYME DUE
TO THE PRESENCE OF THE LESION.
AND IF ANY ERROR-FREE REPAIR
SHOULD OCCUR,
THE PLASMID WILL BECOME CLEAVABLE.
SO WHEN HE FIRST
USED THIS ASSAY TO ASK
WHETHER ANY REPAIR IS GOING ON,
HE ACTUALLY COULD SEE
THAT ABOUT 10 TO 30%,
DEPENDING ON THE DAY
AND THE EXTRACT OF THE INPUT PLASMID
WAS UNDERGOING REPAIR.
HOWEVER, HE THEN VERY QUICKLY UNDERSTOOD
THAT THIS IS DUE TO GLOBAL GENOMIC REPAIR
BECAUSE IF HE DEPLETED XPC,
THE INITIATOR OF THE GLOBAL
GENOMIC PATHWAY
REPAIR WAS ELIMINATED
EVEN UNDER CONDITIONS
WHERE HE WAS ACTIVATING TRANSCRIPTION.
SO IT TOOK US A LITTLE WHILE,
BUT EVENTUALLY
WE REALIZED THAT THIS IS QUITE POSSIBLY
OR PROBABLY DUE,
AT LEAST IN PART TO THE FACT THAT
THE CONCENTRATION OF CLASSIC TC-NER
PROTEINS,
SUCH AS CSB AND CRL4CSA
IN EGG EXTRACT IS VERY LOW.
SO THEREFORE, TYCHO GENERATED
A COCKTAIL OF KNOWN AND SUSPECTED
TC-NER FACTORS THAT'S SHOWN, DOWN HERE.
AND VERY EXCITINGLY, WHEN HE SUPPLEMENTED
THE EGG EXTRACTS WITH THIS COCKTAIL,
THIS SO-CALLED TC-NER COCKTAIL,
HE NOW SAW A MASSIVE BOOST
IN THE EFFICIENCY OF REPAIR,
EVEN UNDER CONDITIONS
WHERE GLOBAL GENOMIC REPAIR
WAS STILL INHIBITED
DUE TO THE REMOVAL OF XPC.
AND HE GOT REALLY EXCITED
WHEN HE FOUND THAT IF HE ALSO NOW
INHIBITED TRANSCRIPTION
USING ALPHA-AMANITIN,
THAT REPAIR CAME BACK DOWN AGAIN.
SO THIS REALLY SUGGESTED
THAT FOR THE FIRST TIME HE COULD OBSERVE,
BONA FIDE, TRANSCRIPTION COUPLED REPAIR.
AND HE WENT ON AND EXPERIMENTS
THAT I WON'T SHOW YOU
TO DEMONSTRATE
THAT THIS TRANSCRIPTION DEPENDENT
REPAIR SIGNAL
THAT HE SEES IS ABSOLUTELY DEPENDENT
ON ALL FOUR OF THE CANONICAL TC-NER FACTORS.
AND SO THAT REALLY
CONVINCED US THAT FOR THE FIRST TIME,
WE HAD BEEN ABLE TO RECAPITULATE
BONA FIDE A TC-NER IN THE TEST TUBE.
AND THIS NOW SET THE STAGE
TO REALLY EMBARK
ON A DETAILED MECHANISTIC ANALYSIS OF,
OF THIS PATHWAY
AND TO TRY TO ADDRESS SOME
OF THE UNANSWERED QUESTIONS.
SO THE FIRST,
QUESTION THAT HE TACKLED WAS TO ADDRESS
THE FUNCTION OF AN OBSCURE
PROTEIN CALLED STK19
THAT STANDS FOR SERINE/THREONINE KINASE 19
AND IS A TOTAL MISNOMER BECAUSE, IN FACT,
THE PROTEIN CONSISTS
OF A SERIES OF WINGED HELIX DOMAINS.
IT HAS NO KINASE FOLD.
IT HAS NO DETECTABLE KINASE ACTIVITY.
HOWEVER, WHAT'S
INTERESTING ABOUT THE PROTEIN
IS THAT IT HAD BEEN CONNECTED
TO TC-NER,
BY VARIOUS GROUPS
IN DIFFERENT INDIRECT WAYS,
THE MOST INTERESTING
OF WHICH PROBABLY IS THAT
IT IS REQUIRED
FOR THE RESUMPTION
OF TRANSCRIPTION AFTER, A UV
INSULT OR CELLULAR UV EXPOSURE
AS SEEN
FOR ESSENTIALLY ALL OTHER CORE
TC-NER FACTORS.
AND IN FACT,
WHEN TYCHO DEPLETED THE PROTEIN
FROM HIS CELL FREE SYSTEM,
HE SAW A COMPLETE ABOLITION OF CELL FREE,
REPAIR,
WHICH HE COULD RESCUE BY ADDING BACK
RECOMBINANT STK19.
SO THIS WAS GREAT.
REALLY ARGUED THAT
THAT, STK19 IS A TRUE
TC-NER REPAIR FACTOR.
AND IT RAISED THE QUESTION
HOW STK19 FUNCTIONS.
NOW, GIVEN THE ABSENCE OF ANY,
CLEARLY
IDENTIFIABLE ENZYMATIC ACTIVITY,
THE NULL HYPOTHESIS BECAME THAT STK19
FUNCTIONS IN TC-NER
ARE BY INTERACTING WITH OTHER PROTEINS.
AND SO, AS YOU ALL KNOW, IDENTIFYING
FUNCTIONALLY RELEVANT PROTEIN
PROTEIN INTERACTIONS IS VERY DIFFICULT.
TYPICALLY ONE MIGHT DO AN
IP MASS SPEC EXPERIMENT
AND LOOK FOR
THINGS THAT CO-IP
WITH, WITH ONE'S PROTEIN OF INTEREST.
BUT THEN THERE'S A LONG ROAD,
IN TERMS OF
VALIDATING WHICH OF THE MANY PROTEINS
ONE ONE RECOVERS
AS ACTUALLY BEING FUNCTIONALLY RELEVANT.
AND THAT OFTEN INVOLVES
AN ELABORATE STRUCTURE
FUNCTION ANALYSIS,
DOMAIN MAPPING AND, AND SO FORTH.
AND THIS CAN REALLY BE A VERY,
VERY LONG AND DIFFICULT PROCESS.
AND SO OVER THE LAST COUPLE OF YEARS,
STIMULATED BY THE STRUCTURE
PREDICTION REVOLUTION,
WE ASKED WHETHER WE CAN
MAKE SORT OF A HAIL
MARY PLAY
AROUND THE CONVENTIONAL APPROACHES
AND ACTUALLY HARNESS
THE STRUCTURE
PREDICTION REVOLUTION TO IDENTIFY
FUNCTIONALLY RELEVANT
PROTEIN-PROTEIN INTERACTIONS AND
THIS IS THE WORK OF A VERY TALENTED
GRADUATE STUDENT, ERNST SCHMID.
AND ESSENTIALLY
WHAT HE DID WAS TO USE THE,
DEEP LEARNING STRUCTURE
PREDICTION ALGORITHM.
ALPHAFOLD-MULTIMER, A COUSIN OF ALPHAFOLD
WHO'S REALLY, DEDICATED FUNCTION
IS TO SOLVE THE STRUCTURE
OF KNOWN PROTEIN-PROTEIN INTERACTIONS.
AND THAT'S OBVIOUSLY SUPER USEFUL.
AND THAT'S
WHAT ALPHAFOLD-MULTIMER WAS DESIGNED FOR.
BUT WHAT ERNST REALIZED, TOGETHER WITH,
SEVERAL OTHER GROUPS LIKE THE BAKER LAB
THE ELOFFSON LAB AND ALSO DAN
DUROCHERS LAB,
WAS THAT
PERHAPS ONE COULD USE
THIS STRUCTURE PREDICTION
APPROACH TO ACTUALLY IDENTIFY
NEW PROTEIN-PROTEIN INTERACTIONS.
AND THE WAY THAT ERNST DOES
THIS IS TO TAKE A BAIT PROTEIN
AND THEN FOLD IT WITH,
A LARGE NUMBER
OF SO-CALLED PREY PROTEINS
AND BASICALLY GENERATE
BINARY STRUCTURE PREDICTIONS
OF EACH PAIR USING ALPHAFOLD-MULTIMER,
AND THEN, USE THE
CONFIDENCE METRICS THAT ALPHAFOLD
PUTS OUT TO PRIORITIZE THESE
ALL OF THESE PREDICTIONS.
AND ESSENTIALLY TO ASK
WHICH OF THESE
IS MOST LIKELY
TO BE A FUNCTIONALLY
RELEVANT INTERACTION?
AND I'M NOT GOING TO GO
INTO THE TECHNICAL DETAILS OF
THE ALPHAFOLD CONFIDENCE METRICS
THAT ARE LISTED HERE,
THINGS LIKE IPTM, PLDDT AND SO FORTH
JUST BECAUSE IT DOESN'T
ADD MUCH TO THE DISCUSSION.
BUT I WILL TELL YOU THAT FOR THESE
AT LEAST
FOR THESE LIMITED SCREENS,
THESE HAVE BEEN REALLY QUITE USEFUL
IN IDENTIFYING
FUNCTIONALLY RELEVANT INTERACTIONS.
AND SO SPURRED BY SOME EARLY SUCCESSES
THAT I'LL TELL YOU ABOUT IN A MOMENT,
ULTIMATELY, WE ACTUALLY WENT AHEAD
AND FOLDED
300 CORE GENOME MAINTENANCE PROTEINS
WITH EACH OTHER,
GENERATING A MATRIX OF ABOUT 40,000 PAIRS
THAT WE MADE FREELY AVAILABLE
AT THIS WEBSITE
CALLED PREDICTOMES.ORG,
WHICH HOPEFULLY MANY OF YOU HAVE SEEN
AND AND AND ARE ACTUALLY USING AND
I WILL
TRY TO ILLUSTRATE THE
POWER OF THIS RESOURCE
USING ONE EXAMPLE
BEFORE I COME BACK TO THE STK19 STORY.
SO ONE OF THE
THE EARLIEST SUCCESS STORIES
FOR US WAS USING STRUCTURE PREDICTION
TO IDENTIFY
FUNCTIONALLY RELEVANT PARTNERS
AND THEREFORE
THE FUNCTION OF A PROTEIN CALLED DONSON.
AND SO THAT PROTEIN
HAD BEEN IMPLICATED
IN SOME ASPECT OF DNA
REPLICATION PREVIOUSLY.
BUT WHAT IT REALLY DOES
WAS QUITE OBSCURE.
AND SO IN THIS STRUCTURE
PREDICTION RESOURCE
THAT WE'VE CREATED,
YOU CAN, CLICK ON YOUR FAVORITE PROTEIN
AND THEN RETRIEVE A PRIORITIZED LIST
BASED ON THE ALPHAFOLD CONFIDENCE METRICS
OF THE LIKELY OR POSSIBLE INTERACTORS.
AND IN THE CASE OF DONSON,
THE RESULTS WERE REALLY QUITE STRIKING.
SO IN THIS LIST OF 300 PROTEINS,
THE TOP 5 OR 6 PROTEINS,
ALL INVOLVED FACTORS
THAT HAD PREVIOUSLY BEEN IMPLICATED
IN THE ASSEMBLY OF THE REPLICATIVE
CMG HELICASE,
WHICH CONSISTS OF THE MCM
TWO THROUGH SEVEN ATPASE,
AND THEN THESE TWO ATPASE
COFACTORS GINS AND CDC45.
SO WHAT ALPHAFOLD SUGGESTED
WAS THAT DANCING INTERACTS WITH TOPB1
FACTOR,
PREVIOUSLY KNOWN TO BE REQUIRED
FOR CMG ASSEMBLY
MCM3, ONE OF THE MCM
TWO THROUGH SEVEN SUBUNITS.
SLD
FIVE ONE OF THE GINS SUBUNITS
AND DNA POLYMERASE EPSILON
THE SECOND SUBUNIT,
WHICH IN YEAST
AT LEAST HAS BEEN IMPLICATED
IN CMG ASSEMBLY.
SO YOU CAN CLICK ON ANY
ONE OF THESE PARTNERS AND RETRIEVE
THE ACTUAL STRUCTURE PREDICTION, WHICH,
HAS ATOMIC RESOLUTION.
AND WHEN WE TOOK ALL OF THESE PREDICTIONS
AND ASSEMBLED THEM
INTO A SINGLE PICTURE, THE
OR A POSSIBLE MECHANISM OF HOW DONSON
AND PROMOTE
CMG ASSEMBLY
REALLY QUITE LITERALLY
LEAPT OFF THE PAGE.
AND THAT WAS THAT DONSON WOULD ORGANIZE
TOPBP1, GINS
AND POL EPSILON INTO WHAT WE NOW
CALL A PRE-LOADING COMPLEX,
AND THAT IT WOULD USE,
ITS PREDICTED INTERACTION
WITH MCM THREE TO REALLY GUIDE THE GINS
HELICASE SUBUNIT
TO ITS PRECISE LOCATION ON THE HELICASE
AND THROUGH,
A LONG SERIES OF STRUCTURE FUNCTION.
EXPERIMENTS
WHERE WE MUTATED THE PREDICTED INTERFACES
AND ASKED WHETHER THE PRELOADING
COMPLEX STILL FORMS
AND WHETHER REPLICATION STILL OCCURS.
WE WERE ABLE TO PROVIDE
COMPELLING SUPPORT FOR THIS MODEL.
AND I SHOULD ALSO MENTION
THAT THIS WAS ONE OF THESE
PERFECT STORM SITUATIONS
WHERE A NUMBER OF OTHER GROUPS ALSO,
WERE ABLE TO IMPLICATE DONSON
IN THE ASSEMBLY OF CMG.
AND SOME OF THESE GROUPS ACTUALLY ALSO,
PROVIDED EXPERIMENTAL STRUCTURE
DETERMINATION THAT AGREED VERY NICELY
WITH, WITH THE STRUCTURE PREDICTION.
SO THIS WAS A REALLY GRATIFYING CASE
WHERE WE WERE ABLE TO USE THIS IN SILICO
SCREENING APPROACH
TO IDENTIFY FUNCTIONALLY RELEVANT
INTERACTORS OF AN OBSCURE PROTEIN,
SUCH AS DONSON.
SO, NOW I'LL TELL YOU ABOUT
SORT OF, I GUESS THE SIMILAR STORY
WHERE WHERE
THIS IN SILICO SCREENING APPROACH
REALLY CRACKED
OPEN THE,
THE QUESTION OF HOW STK19 PROMOTES TC-NER.
SO WHEN WE LOOKED
AT THE LIST,
THE PRIORITIZED LIST
OF PREDICTED STK19 INTERACTORS,
THE REALLY STRIKING FACT
WAS THAT AMONG THE 300
GENOME MAINTENANCE PROTEINS,
THE TOP TWO HITS
WERE THE CSA SUBUNIT OF THE CRL4CSA
LIGASE,
AND THE XPD SUBUNIT OF THE TFIIHIIH COMPLEX.
AND THIS PRETTY MUCH IMMEDIATELY
SUGGESTED A POSSIBLE MECHANISM
BY WHICH
STK19 PROMOTES TC-NER,
AND THAT IS TO INCORPORATE
INTO THE TC-NER COMPLEX
AND THEN USE THE PROTEIN
PROTEIN INTERACTION WITH XPD TO, RECRUIT
OR AT LEAST POSITION TFIIH
IN SUCH A WAY
THAT XPD IS GUIDED
TO THE TEMPLATE STRAND.
SO IN ORDER TO ACTUALLY
TO TEST THE VALIDITY OF THIS MODEL,
WE DID A FEW THINGS.
THE FIRST,
I'LL FOCUS ON THE FIRST PART OF IT,
WHICH IS THE IDEA THAT STK19 FORMS
PART OF THE TC-NER COMPLEX.
AND WE DID TWO THINGS.
THE FIRST
THAT WE COULD
INITIATE IMMEDIATELY, ONCE WE HAD
THE PREDICTION, WAS TO MUTAGENIZE
THE PREDICTED INTERFACE,
GUIDED BY THE ACTUAL MOLECULAR
RESOLUTION STRUCTURE PREDICTION.
AND WHEN WE MADE MUTATIONS IN STK
19 THAT ARE PREDICTED
TO DISRUPT THE INTERACTION WITH CSA,
THE RESULTING STK19
MUTANT WAS TOTALLY INACTIVE
FOR CELL FREE TC-NER.
SO THAT WAS CONSISTENT WITH THE IDEA.
BUT WE ACTUALLY,
WERE REALLY, REALLY LUCKY
THAT WE WERE ABLE TO
THEN COLLABORATE
WITH MY COLLEAGUE LUCAS,
FARNUNG IN THE CELL BIOLOGY DEPARTMENT.
AND, HE HAD PRETTY MUCH EVERYTHING
LYING AROUND, IN HIS FREEZERS
THAT WAS NEEDED
TO ASSEMBLE THE TC-NER COMPLEX.
AND WE GAVE HIM STK19 AND ALL TOGETHER.
THEN HE WAS ABLE TO SOLVE
A, A CRYO-EM STRUCTURE OF AN STK19
CONTAINING TC-NER
COMPLEX AT A REALLY IMPRESSIVE
RESOLUTION OF 1.9 ANGSTROM, AND THAT
VERY, BEAUTIFULLY CONFIRMED
THE INTERACTION OF STK19 WITH CSA.
SO, THAT STRUCTURE LOOKS ALMOST EXACTLY,
AS PREDICTED BY ALPHAFOLD.
BUT IT ALSO SHOWED THAT STK19
CAN BIND SIMULTANEOUSLY
WITH CSA AND RBP1,
AND THAT IT ALSO MAKES CLOSE CONTACT
WITH THE DOWNSTREAM DNA, THAT IS, THE DNA
THAT IS IN THE DIRECTION OF, OF MOVEMENT
BEFORE RNA POLYMERASE GETS STALLED.
SO SO THIS REALLY SUPPORTED THE IDEA
THAT STK19
IS AN INTEGRAL
STRUCTURAL COMPONENT OF THE TC-NER COMPLEX.
AND SO NOW WE WANTED
TO TEST THE OTHER IDEA,
WHICH IS THAT STK19 RECRUITS TFIIH.
AND AGAIN
WE STARTED WITH A MUTAGENESIS
GUIDED BY THE STRUCTURE PREDICTION.
AND AGAIN
WE FOUND THAT WHEN WE MUTAGENIZE
THIS INTERFACE
THAT THE RESULTING STK19 PROTEIN
WAS LARGELY INACTIVE FOR CELL FREE TC-NER.
NOW, WE WOULD OF COURSE
LOVE TO ALSO SOLVE THE STRUCTURE
OF THIS ENTIRE ASSEMBLY,
AND WE ARE WORKING ON THAT.
BUT IN THE INTERIM,
WHAT WE DID WAS TO ACTUALLY MODEL
HOW THIS, THIS ASSEMBLY MIGHT LOOK.
AND THE WAY THAT WE DID
THAT WAS TO START
WITH THE CRYO-EM STRUCTURE OF THE SDK
19 CONTAINING TC-NER COMPLEX.
AND WE THEN TOOK THE ALPHAFOLD PREDICTION
OF THE STK19 PD INTERACTION.
AND WE ALIGNED IT
TO THE CRYO-EM STRUCTURE
USING THE STK19 SUBUNIT ON THE ONE HAND.
AND THEN ON THE OTHER HAND,
WE TOOK A PREVIOUSLY DETERMINED AGAIN
BY THE KRAMER LAB
CRYO-EM STRUCTURE
OF THE ENTIRE TFIIH COMPLEX IN ASSOCIATION
WITH A SPLAYED DNA
SUBSTRATE THAT SORT OF MIMICS
THE TFIIH COMPLEX IN THE ACT OF LESION
VERIFICATION.
HERE, YOU CAN SEE THE SINGLE STRANDED,
DNA GOING THROUGH THE XPD HELIX,
AND WE ALIGNED THIS COMPLEX ON THE PRIOR
ASSEMBLY USING THE XPD SUBUNIT.
AND IF YOU LOOK AT THIS IN DETAIL,
THE STRIKING FACT IS THAT THE 3’
END OF THE SINGLE STRAND
EMERGING FROM XPD,
THAT IS THE STRAND THAT IS UNDERGOING
LESION VERIFICATION,
OR AT LEAST MIMICKING
THE PROCESS OF LESION
VERIFICATION, IS VERY CLOSELY JUXTAPOSED
WITH THE 5’
END OF THE TEMPLATE STRAND
THAT IS PART OF THE
THE STALLED, TC-NER COMPLEX.
SO THIS IS REALLY ENTIRELY
CONSISTENT WITH THE IDEA
THAT STK
19 REALLY GUIDES THE TFIIH COMPLEX
TO THE RIGHT POSITION, SO THAT AFTER
XPB UNWINDS THE DUPLEX, XPD
WOULD BE ABLE TO ENGAGE
WITH THE TEMPLATE STRAND.
AND SO IN OTHER WORDS,
WE REALLY THINK NOW THAT STK19
IS THE MISSING LINK
BETWEEN THE TC-NER COMPLEX
AND THE DOWNSTREAM
TFIIH DEPENDENT LESION
VERIFICATION PROCESS.
AND SO IF WE NOW THINK ABOUT THIS
IN TERMS OF, YOU KNOW, THE WHOLE MODEL,
WHAT WE'RE THINKING
IS THAT AFTER RNA POLYMERASE
STALLS AT A LESION,
THERE IS THE ASSEMBLY OF THE TC-NER COMPLEX
THAT WE NOW APPRECIATE INCLUDES STK19.
THE NEXT STEP IS THE RECRUITMENT OF
TFIIH
AND I DIDN'T MENTION THIS BEFORE,
BUT I'LL MENTION IT NOW.
SEVERAL GROUPS HAVE SHOWN THAT
IN ORDER TO RECRUIT
TFIIH TO A TC-NER COMPLEX,
YOU ACTUALLY REQUIRE
AN INTERACTION
BETWEEN THE P62 SUBUNIT OF TFIIH
AND THIS TFIIH INTERACTING REGION IN,
A SHORT PEPTIDE
THAT SITS
ON AN UNSTRUCTURED
LOOP OF THE UVSSA PROTEIN.
SO WE ACTUALLY THINK THAT UVSSA IS
THE SORT OF INITIAL CAPTURE
POINT FOR TFIIH.
BUT WE BELIEVE THAT THE PROTEIN
PROTEIN INTERACTION
BETWEEN STK19 AND XPD IS WHAT ULTIMATELY
PROPERLY POSITIONS TFIIH IN PRECISELY
THE CONFIGURATION THAT IS NEEDED
FOR PRODUCTIVE LESION VERIFICATION.
AND OF COURSE, THE DOWNSTREAM EVENTS
THEN ARE ASSEMBLY OF AN INCISION
COMPLEX AND GAP FILLING.
NOW, I WOULD LIKE TO, POINT OUT
ONE ASPECT OF THIS
THAT IS DESCRIBED IN DETAIL
IN TYCHO'S PAPER.
I DON'T HAVE TIME TO SHOW YOU THE DATA,
BUT I WANT TO POINT OUT
THAT ACTUALLY THE CRYO-EM STRUCTURE
OF THE STK19 CONTAINING TC
NER COMPLEX REALLY SHOWS THAT,
THE THE VHS DOMAIN OF UVSSA
ACTUALLY BLOCKS THE SITE ON STK19,
WHERE XPD WOULD NORMALLY BE RECRUITED.
AND SO THAT WAS A BIT OF A PARADOX.
BUT THEN WE REALIZED THAT ACTUALLY
UVSSA INTERACTS WITH THIS FLEXIBLE,
C-TERMINAL TAIL OF CSA
THAT WE THINK ALLOWS UVSSA
TO SWING OUT OF THE WAY
TO MAKE ROOM FOR XPD.
AND IN FACT, WE MADE A SINGLE POINT
MUTATION IN THIS C-TERMINAL TAIL OF CSA,
THAT WE SHOWED TOTALLY DISRUPTS THE,
THE ABILITY OF CSA TO SUPPORT,
TC-NER, IN TOTAL AGREEMENT WITH,
WITH THIS MODEL.
SO THAT WAS ONE,
SORT OF ADDITIONAL WRINKLE
THAT I WANTED TO POINT OUT.
NOW, THERE ARE OTHER, SORT OF
OBVIOUS QUESTIONS
THAT THAT RESULT FROM THIS MODEL,
ONE OF WHICH IS HOW THE SO-CALLED CAK
DOMAIN OF THE TFIIH COMPLEX IS REMOVED.
SO IT'S KNOWN THAT THE CAK
DOMAIN IS REQUIRED FOR TFIIH,
ITS FUNCTION IN TRANSCRIPTION INITIATION,
BUT IT'S ACTUALLY INHIBITORY
FOR TC-NER AND HAS TO BE REMOVED.
AND, THE QUESTION IS,
AT WHAT STAGE OF THIS RECRUITMENT
OR THIS CAPTURE AND DOCKING,
PATHWAY FOR TFIIH
THE CAK MODULE IS REMOVED
AND THAT'S SOMETHING
THAT WE ARE ACTIVELY THINKING ABOUT.
AND THEN OF COURSE,
YOU KNOW, BACK TO
SOME OF THE CLASSIC QUESTIONS
LIKE WHAT DOES RNA POLYMERASE
ACTUALLY DO?
WHAT IS ITS FATE
DURING DURING THESE, VARIOUS,
REPAIR STEPS?
DOES IT DOES IT BACKTRACK AND RESTART
OR IS IT REMOVED?
THESE ARE ALSO VERY,
I THINK INTERESTING QUESTIONS THAT
THAT PERHAPS NOW BECOME TRACTABLE.
OKAY.
SO THAT'S
WHAT I WANTED
TO TELL YOU ABOUT TC-NER
AND HOW STRUCTURE-PREDICTION
REALLY ACCELERATED OUR PROGRESS IN
IN UNDERSTANDING HOW THIS NEW FACTOR,
STK19 PROMOTES THIS REACTION.
BUT WHAT I WANT TO DO IN THE LAST
COUPLE OF MINUTES
HERE IS TO ASK THE QUESTION,
WHAT ARE REALLY
THE LIMITS OF THIS IN SILICO
SCREENING APPROACH?
SO
IN OTHER WORDS,
CONSIDER AN EXTREME SCENARIO
WHERE YOU HAVE A PROTEIN
THAT, YOU FIND INTERESTING
FOR WHATEVER REASON.
BUT LET'S SAY, YOU KNOW
ESSENTIALLY NOTHING ABOUT IT.
COULD YOU ACTUALLY CARRY OUT
A PROTEOME WIDE IN SILICO SCREEN
IN ORDER TO IDENTIFY
FUNCTIONALLY RELEVANT
INTERACTORS, WHICH,
OF COURSE,
WOULD PROBABLY TELL YOU A LOT ABOUT
NOT ONLY THE PATHWAY
IN WHICH THE PROTEIN OPERATES,
BUT ALSO ABOUT ITS MECHANISM.
SO, SO WE WERE VERY CURIOUS ABOUT THIS.
SO WE WENT AHEAD AND ACTUALLY SCALED UP
SOME OF THE SCREENS
THAT I'VE TOLD YOU ABOUT.
SO, WE WENT AHEAD AND FOLDED STK19
WITH ALL 20,000 HUMAN PROTEINS.
AND THEN WE USED VARIOUS METRICS TO ASK,
WHERE
IN THIS LIST OF 20,000
BINARY STRUCTURE PREDICTIONS,
WOULD THE FUNCTIONALLY RELEVANT PARTNERS
THAT WE NOW,
KNOW ABOUT,
WHERE WOULD THEY SIT IN THIS RANK LIST?
AND SO IF YOU TAKE ONE OF THE,
VERY POPULAR CONFIDENCE METRICS
CALLED PDOCKQ,
THE RESULTS ARE REALLY QUITE TERRIBLE.
SO THE,
THE FUNCTIONALLY RELEVANT PARTNERS, CSA,
WHICH ALSO GOES BY THE NAME OF ERCC8
AND XPD,
WHICH GOES BY THE NAME OF ERCC2,
AS WELL AS RNA POLYMERASE
ARE, YOU KNOW, NOWHERE NEAR THE TOP.
OKAY. SO THAT LOOKS PRETTY BAD.
IPTM DOES A LOT BETTER.
SO NOW THESE THREE FUNCTIONALLY
RELEVANT
PARTNERS ARE IN THE TOP 60 OR SO, PAIRS.
SO THAT'S REALLY QUITE GOOD.
BUT, YOU KNOW, STILL MAYBE
NOT GOOD ENOUGH
IF YOU DIDN'T KNOW ANYTHING
ABOUT THE PROTEIN.
WE DID ANOTHER EXAMPLE.
SO REMEMBER THE DONSON PROTEIN
THAT IS REQUIRED
FOR CMG HELICASE
ASSEMBLY AND THAT INTERACTS
FUNCTIONALLY
WITH, THESE 4 OR 5 FACTORS HERE.
IF YOU USE PDOCKQ,
THE RESULTS ARE REALLY PRETTY TERRIBLE.
IF YOU USE IPTM, IT GETS BETTER.
BUT YOU KNOW, THE
THE FIVE PARTNERS
HERE ARE SPREAD OVER THE TOP 1000 HITS.
AND AND SO AGAIN,
THAT'S NOT TERRIBLY USEFUL
IF YOU DON'T KNOW MUCH ABOUT THE PROTEIN
TO BEGIN WITH.
SO FOR THIS FOR US,
THIS REALLY SUGGESTED THAT WE NEED BETTER
CONFIDENCE METRICS
TO IDENTIFY
FUNCTIONALLY RELEVANT INTERACTORS.
SO WHAT WE DID WAS TO ACTUALLY USE
SORT OF
CLASSICAL MACHINE
LEARNING APPROACHES TO TRAIN A CLASSIFIER
THAT WE HOPED WOULD BE ABLE TO TELL
THE DIFFERENCE BETWEEN
FUNCTIONAL
ALPHAFOLD PREDICTIONS
AND SPURIOUS ALPHAFOLD PREDICTIONS.
AND SO WE USED,
YOU KNOW, THE
CLASSIC, APPROACH,
WHICH IS TO ACTUALLY TRAIN A CLASSIFIER
ON A A SET OF KNOWN DATA POINTS.
SO WE TOOK A LARGE NUMBER OF ALPHAFOLD
BINARY ALPHAFOLD PREDICTIONS,
THE VAST
MAJORITY OF WHICH WE KNEW TO BE NEGATIVE
BECAUSE THEY CORRESPONDED
TO COMPLETELY RANDOM PAIRINGS,
AS WELL AS A SET OF PAIRS.
ALPHAFOLD BINARY
STRUCTURE PREDICTIONS
THAT WE PRESUMED TO BE POSITIVE
BECAUSE THEY CORRESPOND TO PROTEIN PAIRS
THAT ACTUALLY CROSS
LINK IN VIVO
IN CROSSLINKING MASS SPEC EXPERIMENTS.
SO WE MIXED THESE TOGETHER,
AND THEN WE TRY TO TRAIN A CLASSIFIER
THAT IS INFORMED BY,
A NUMBER OF DIFFERENT FEATURES.
AND SO THESE FEATURES
THAT WE FED THE CLASSIFIER FALL
INTO TWO DIFFERENT GROUPS.
ONE WE CALL STRUCTURAL FEATURES.
SO THESE
ARE NOT ONLY THE
ALPHAFOLD DERIVED CONFIDENCE METRICS
THAT COME WITH EVERY BINARY
STRUCTURE PREDICTION IPTM, PIDDT
AND SO FORTH,
BUT ALSO MEASURABLE PROPERTIES OF THE
PREDICTIONS THEMSELVES.
SO HOW MANY HYDROGEN AND SALT BRIDGES,
ARE AT THE INTERFACE?
WHAT IS THE SIZE OF THE,
OF THE INTERFACE AND SO FORTH?
AND WE ACTUALLY INITIALLY
TRAINED A CLASSIFIER
USING ONLY THESE STRUCTURAL FEATURES.
AND ITS PERFORMANCE
WAS WAS DECENT,
BUT NOT QUITE WHERE WE WANTED IT TO BE.
SO WE THEN REASONED THAT
PERHAPS WE ALSO NEED TO BE LOOKING
AT THE BIOLOGICAL PROPERTIES
OF ALL OF THE PROTEIN.
PAIRS THAT WE'RE LOOKING AT.
AND SO WE THEN ALSO CONSIDERED,
OMICS DERIVED BIOLOGICAL FEATURES
SUCH AS CO-EXPRESSION DATA, CO-LOCALIZATION.
ARE THE TWO PROTEINS AND THE PAIR,
DO THEY SHOW A SIMILAR DEPENDENCY
AND THE THOUSAND
OR SO
GENOME WIDE CRISPR SCREENS
THAT HAVE BEEN REPORTED?
IS THERE EVIDENCE
FOR ASSOCIATE
ASSOCIATION IN BIOGRID, ETC.?
AND WHEN WE USED BOTH THESE
STRUCTURAL AND BIOLOGICAL FEATURES
TO INFORM, AND TRAIN A,
A CLASSIFIER, A RANDOM FOREST CLASSIFIER
TO BEST SEPARATE,
THE POSITIVES AND THE NEGATIVES,
WE ACTUALLY ENDED UP WITH A CLASSIFIER
THAT WAS REALLY QUITE USEFUL.
SO, IN THESE MACHINE
LEARNING APPROACHES,
ONE TYPICALLY TAKES 75% OF THE,
OF THE, OF THE DATA, THE, THE KNOWN
DATA POINTS TO TRAIN.
AND THEN ONE USES THE REMAINING 25%
TO ACTUALLY TEST PERFORMANCE.
AND, I WILL
JUST VERY BRIEFLY TELL YOU
THAT, GUIDED IN LARGE PART
BY SOME VERY CONSCIENTIOUS
AND VERY RIGOROUS, COMPUTATIONAL
BIOLOGY REVIEWERS OF OUR MANUSCRIPT,
WE PUT OUR CLASSIFIER
THROUGH ALL OF THE PACES,
AND,
AND DID
A LOT OF THE PERFORMANCE TESTING,
INCLUDING,
RUNNING
THESE ROC CURVES
AND MEASURING THE AREA UNDER THE CURVE,
WHICH, I HOPE YOU CAN SEE HERE,
SHOWS THAT OUR CLASSIFIER,
WHICH WE CALL SPOC,
PERFORMS,
REALLY QUITE WELL
AND MUCH BETTER THAN
THE PREVIOUS CONFIDENCE METRICS.
BUT I'LL SHOW YOU A MUCH MORE INTUITIVE
PERFORMANCE TEST IN A MOMENT.
BUT I WILL POINT OUT, THAT, WE CALL IT
WE CALL IT SPOC,
NOT ONLY BECAUSE IT'S A CUTE ACRONYM,
BUT BECAUSE REALLY
THE CLASSIFIER TAKES INTO CONSIDERATION
NOT ONLY THE STRUCTURAL FEATURES
OF THE PROTEIN PAIRS,
BUT ALSO, A LONG LIST OF OMICS
DERIVED BIOLOGICAL FEATURES OF EACH PAIR.
AND IT'S REALLY BY COMBINING,
BOTH OF THESE, THESE PROPERTIES.
SO CONSIDERING
NOT ONLY THE STRUCTURAL PLAUSIBILITY
OF THE STRUCTURE PREDICTION,
BUT ALSO THE BIOLOGICAL PROPERTIES
OF THE PROTEINS INVOLVED,
THAT WE WERE ABLE TO GENERATE
A CLASSIFIER, THAT PERFORMS REALLY WELL,
AND TO CONVINCE YOU THAT IT PERFORMS
WELL, I WILL REVISIT
THESE PROTEOME WIDE SCREENS
AND SHOW YOU THAT UNLIKE THE,
CLASSIC CONFIDENCE METRICS PDOCKQ AND IPTM,
WHICH REALLY SPREAD
THE FUNCTIONALLY RELEVANT PARTNERS
OVER A LARGE,
LIST OF PRESUMABLY FALSE POSITIVES,
SPARK
REALLY DOES AN AMAZING JOB OF PUTTING
THE FUNCTIONALLY RELEVANT PARTNERS
AT THE VERY TOP
OF THIS LIST OF 20,000 BINARY.
PREDICTIONS.
WE SEE THE SAME THING FOR DONSON.
SO HERE ARE THE FIVE OR SO, FUNCTIONAL.
RELEVANT
PARTNERS ARE SPREAD OVER
THE TOP
SEVEN HITS IN THIS PROTEOME WIDE SCREEN.
AND WE'VE ACTUALLY REPEATED,
VERSIONS OF THESE PROTEOME
WIDE SCREENS OVER, WE'VE DONE THIS
ABOUT 30 TIMES AND SPOC CONSISTENTLY
PERFORMS REALLY WELL,
INCLUDING ON PROTEINS
THAT ARE NOT IN THE DNA DAMAGE
RESPONSE, BUT, OPERATE IN THE CYTOPLASM,
AND VARIOUS DIFFERENT ORGANELLES.
AND THAT ACTUALLY MAKES SENSE
BECAUSE NOTHING ABOUT SPOC'S
TRAINING WAS ACTUALLY, REALLY PATHWAY
SPECIFIC.
OKAY.
SO NOW THAT WE HAVE A CLASSIFIER
THAT CAN ACTUALLY PICK OUT
FUNCTIONALLY RELEVANT
STRUCTURE PREDICTIONS
OUT OF A TRULY PROTEOME WIDE SCREEN,
IN PRINCIPLE,
WE'RE NOW IN A POSITION
TO ACTUALLY TRY TO GENERATE
A COMPREHENSIVE STRUCTURAL INTERACTOME.
AND SO THAT WOULD REALLY INVOLVE
TAKING ALL 20,000 HUMAN PROTEINS
AND PAIRING THEM UP WITH EACH OTHER,
FOLDING EACH PAIR.
AND THEN
APPLYING THE SPOC CLASSIFIER
THAT ACTUALLY WOULD INVOLVE
200 MILLION POSSIBLE PAIRS.
SOMETHING LIKE 0.1% OF
THESE ARE THOUGHT TO BE,
ACTUALLY FUNCTIONAL.
SO IT'S IT'S REALLY LOOKING
FOR A NEEDLE IN A HAYSTACK,
WHICH WE THINK, SPOC IS EQUIPPED TO DO.
HOWEVER, THERE IS OBVIOUSLY ONE
MAJOR BARRIER,
AND THAT IS THE COMPUTE
THAT WOULD BE NEEDED TO
TO COMPUTE THIS ENTIRE MATRIX.
SO THIS WOULD COST
TENS OF MILLIONS OF DOLLARS
IN, IN CLOUD COMPUTE COMPUTING.
AND SO WHAT WE AND OTHERS
ARE DOING TO MAKE THIS SORT
OF AN APPROACHABLE
PROBLEM IS TO INTRODUCE A TRIAGE STEP.
AND I'M HAPPY TO DISCUSS
HOW WE'RE DOING THIS.
BUT THE THE IDEA IS TO USE
MUCH LESS COMPUTATIONALLY
INTENSIVE APPROACHES
TO NOMINATE A SMALL SUBSET OF THE 200
MILLION PAIRS,
LET'S SAY THE TOP 1% OR 2 MILLION,
AND THEN SUBJECT
THOSE TO A FULL ANALYSIS WITH ALPHAFOLD
AND THE, THE SPOC CLASSIFIER.
AND WE'RE ACTUALLY GETTING,
VERY GENEROUS SUPPORT
FROM NVIDIA CORPORATION TO,
TO FOLD ABOUT 2 MILLION PAIRS,
WHICH WE HOPE WILL LEAD TO AT LEAST
A FIRST DRAFT
OF A REASONABLE STRUCTURAL INTERACTOME
THAT WE THINK,
TOGETHER WITH THE EFFORTS OF OTHER LABS
LIKE THE CONG LAB AT UT SOUTHWESTERN,
WILL, YOU KNOW, BEGIN TO GENERATE
A USEFUL STRUCTURAL INTERACTOME
THAT CAN CATALYZE
A LOT OF MECHANISTIC
DISCOVERY IN THE FIELD.
SO, UNTIL
WE HAVE THAT AND AND THAT'S, YOU KNOW,
GOING TO BE A LITTLE BIT OF,
IT'S GOING TO TAKE SOME TIME TO,
TO COMPLETE THE FOLDING.
WE'RE ABOUT IN THE MIDDLE OF THE RUN
RIGHT NOW.
AND IT'S GOING TO REQUIRE
QUITE A BIT OF ANALYSIS.
BUT IN THE MEANTIME,
THERE ARE ACTUALLY RESOURCES
THAT THAT YOU CAN UTILIZE, ALREADY.
SO THE PREDICTIVE, SORT RESOURCE,
WHICH IS REALLY DEDICATED TO,
THE GENOME MAINTENANCE PATHWAY.
AND I'D ALSO LIKE TO POINT OUT
THAT THE CONG LAB AT UT
SOUTHWESTERN HAS ACTUALLY ALREADY,
TAKEN A FIRST SWING
AT A STRUCTURAL INTERACTOME AND,
PUBLISHED A BIORXIV PAPER,
AND THEY HAVE THIS VERY NICE WEB RESOURCE
WHERE YOU CAN TYPE
IN YOUR FAVORITE PROTEIN,
AND THEY HAVE NOMINATED ABOUT 8000 NEW,
VERY HIGH QUALITY, HIGH
CONFIDENCE PROTEIN-PROTEIN INTERACTIONS.
WE'VE LOOKED AT THE DATABASE.
IT'S IT'S IT'S EXCELLENT.
BUT STILL OF COURSE, VERY INCOMPLETE.
BUT THIS IS DEFINITELY A STARTING POINT
FOR ALL OF YOU TO START LOOKING FOR
FUNCTIONALLY RELEVANT
INTERACTORS OF YOUR FAVORITE PROTEINS.
OF COURSE,
YOU CAN DO
YOUR OWN PROTEIN FOLDING EXPERIMENTS.
ESPECIALLY NOW THAT DEEPMIND
HAS MADE AVAILABLE,
THIS VERY USER FRIENDLY,
WEB INTERFACE WHERE YOU CAN,
USE THE ALPHAFOLD ALGORITHM
TO LOOK NOT ONLY FOR PROTEIN
PROTEIN INTERACTIONS,
BUT ALSO PROTEIN NUCLEIC ACID
AND PROTEIN LIGAND INTERACTIONS.
AND IF YOU HAVEN'T USED THIS ALREADY,
I STRONGLY ENCOURAGE YOU.
IT'S A BIT
LIMITED IN HOW MANY, EXPERIMENTS
YOU CAN DO, BUT YOU CAN
ACTUALLY, YOU KNOW,
IF YOU
IF YOU COLLECT
A COUPLE OF GOOGLE, ACCOUNTS
AND DO IT OVER A FEW DAYS,
YOU CAN EASILY FOLD A FEW HUNDRED
PAIRS AND DO A MINI SCREEN.
AND, YOU KNOW, IF THE WHOLE,
ALPHAFOLD BUSINESS
IS INTIMIDATING FOR YOU,
AND IF YOU'RE NOT SURE
ABOUT THE CONFIDENCE METRICS
AND SO FORTH, THE,
THE EUROPEAN BIOINFORMATICS
INSTITUTE HAS SOME VERY NICE
RESOURCES, INCLUDING,
A REALLY GREAT TUTORIAL
THAT THAT REALLY, GIVES,
A VERY NICE INTRODUCTION TO,
TO ALPHAFOLD
AND THE CONFIDENCE METRICS AND SO FORTH.
SO I'D LIKE TO END BY
REALLY JUST POINTING OUT THAT I THINK
WITH THE STRUCTURE PREDICTION REVOLUTION,
THERE IS A REALLY DRAMATIC
DEMOCRATIZATION OF STRUCTURAL BIOLOGY
THAT IS UNDERWAY.
I THINK UNTIL RECENTLY,
THERE WAS SORT OF THIS,
YOU KNOW, THIS FIREWALL BETWEEN,
THE PEOPLE WHO,
YOU KNOW, DO GENETICS AND CELL BIOLOGY
AND SOME BIOCHEMISTRY
AND THOSE WHO DO STRUCTURAL BIOLOGY AND
I THINK THAT WITH THE,
YOU KNOW,
THE ADVENT OF ALPHAFOLD
AND OTHER RELATED
ALGORITHMS, ALL OF US,
WHETHER WE'RE
GENETICISTS, CELL BIOLOGISTS, BIOCHEMISTS
OR SOMETHING ELSE,
WE CAN ALL NOW BEGIN
TO REALLY THINK
STRUCTURALLY ABOUT ALL OF THE PROBLEMS
THAT WE WORK ON.
AND,
SO I THINK,
I THINK THIS, THIS WALL
IS COMPLETELY BREAKING DOWN
AND, YOU KNOW, FOR MY LAB
AND I THINK FOR A LOT OF OTHER LABS
NOW, A REALLY TYPICAL
SORT OF WORKFLOW IS TO EITHER,
YOU KNOW, USE THE RESOURCES
THAT I MENTIONED A FEW SLIDES AGO,
OR ONE'S OWN STRUCTURE, PREDICTIONS TO,
TO IDENTIFY POTENTIAL NEW INTERACTIONS,
WHICH IN MANY CASES
LEAD TO A COMPELLING HYPOTHESIS
THAT IS IMMEDIATELY TESTABLE,
YOU KNOW, THROUGH SITE
DIRECTED MUTAGENESIS,
AND STRUCTURE FUNCTION ANALYSIS
WITH, OF COURSE,
THE ULTIMATE GOAL ALWAYS BEING TO CONFIRM
THESE PREDICTIONS
USING STRUCTURE DETERMINATION.
BUT WHAT'S WHAT'S SO POWERFUL
AND SO BEAUTIFUL
ABOUT THE STRUCTURE
PREDICTION, REVOLUTION
IS THAT WE CAN ALL, THINK STRUCTURALLY
AND WE CAN LONG BEFORE WE HAVE
THE REAGENTS
OR THE RESULTS
OF AN EXPERIMENTAL
STRUCTURE DETERMINATION,
WE CAN ACTUALLY, START,
FORMULATING AND TESTING HYPOTHESES.
AND, AND I ALSO WANT TO SAY
THAT, YOU KNOW, FAR
FROM SOMEHOW
PUTTING STRUCTURAL BIOLOGISTS
OUT OF BUSINESS,
I THINK IT'S IN,
IN MANY WAYS
HAVING THE OPPOSITE EFFECT BECAUSE,
SO MANY MORE GROUPS CAN NOW,
FORMULATE
STRUCTURAL HYPOTHESES, YOU KNOW,
FEASIBLE STRUCTURAL HYPOTHESES THAT THAT,
WE'RE NOW
TALKING TO THE STRUCTURAL BIOLOGISTS
ABOUT AND GETTING THEIR HELP TESTING.
SO, SO FOR ME,
YOU KNOW,
IT IS REALLY DRAMATICALLY STRENGTHENED
MY INTERACTION
WITH WITH LOCAL STRUCTURE
DETERMINATION GROUPS.
I DON'T WANT TO LEAVE YOU
WITH TWO ROSY OF A PICTURE.
I WILL POINT OUT THAT THAT ALPHAFOLD
IS NOT INFALLIBLE.
THERE ARE LOTS OF FALSE
NEGATIVE INTERACTIONS
AND STILL SOME FALSE POSITIVES.
THERE ARE ERRORS IN IN RESIDUE
AND DOMAIN POSITIONING
AND OF COURSE, A LIMITED SORT OF,
SURVEY OF THE CONFORMATIONAL DYNAMICS.
SO ALL OF THIS MEANS THAT,
AND TOGETHER WITH,
WITH WHAT I SAID
JUST A MOMENT AGO,
ALL OF THIS MEANS THAT
THAT EXPERIMENTAL STRUCTURE
DETERMINATION IS STILL REALLY
AN ABSOLUTELY ESSENTIAL,
PART OF OF DERIVING,
A DEEP MECHANISTIC
UNDERSTANDING OF ALL THE PROCESSES
THAT WE CARE ABOUT.
SO I'M GOING TO STOP THERE
AND THANK THE PEOPLE WHO DID THE WORK.
SO TYCHO,
REALLY FABULOUS POSTDOC
WHO IS ON THE JOB MARKET.
DID ALL THE EXPERIMENTAL, WORK ON TC-NER
ERNST REALLY LED THE WAY ON THE,
STRUCTURE PREDICTION
SIDE WITH HELP FROM FROM HELEN
AND JACK, TWO UNDERGRADUATES.
AND I WANT TO THANK MY AMAZING
COLLABORATOR LUCAS AND HIS TRAINEES
FOR, JUST BLOWING
OUR MINDS WITH WITH HOW QUICKLY
THEY CAN, ACTUALLY GENERATE
EXPERIMENTAL STRUCTURE.
DETERMINATION TO TO HELP US TEST
WHETHER WE'RE ON THE RIGHT TRACK
WITH OUR, WITH OUR PREDICTIONS.
AND I THINK I'M GOING TO STOP THERE AND,
JUST THANK MY FUNDING SOURCES,
OF COURSE,
AND GIVE ANOTHER SHOUT OUT TO NVIDIA
FOR GENEROUSLY, DONATING GPU TIME TO,
START, START ZIPPING THROUGH,
THESE MANY PREDICTIONS THAT WE WANT TO,
TO GENERATE TO,
TO WORK TOWARDS A STRUCTURAL INTERACTOME.
ALL RIGHT.
SO, I'LL STOP THERE.
I GUESS I'LL STOP SHARING.
THANKS SO MUCH, JOHANNES.
THAT WAS WONDERFUL.
JIM. THANK YOU.
CHUNZHANG DO YOU WANT TO START WITH THE QUESTIONS.
YEAH, SURE.
SO I'LL GO THROUGH THE,
QUESTIONS IN THE CHAT BOX.
SO WE HAVE A QUESTION FROM, MARCELLA.
SAGAR.
WHAT IS THE
ADVANTAGE OF USING ALPHAFOLD
AND MULTIMODE,
TO IDENTIFY
PROTEIN-PROTEIN INTERACTIONS.
ALPHAFOLD MODEL,
POLYMER ASSUME THE PROTEIN IS UNFOLDED
WITHOUT ITS PROTEIN
BINDING PARTNER
AND FOLDED INVOLVES INTERACTION
WITH THE BAIT PROTEIN.
COULD YOU IDENTIFY A NOVEL
BINDING PARTNER ASSUMING
THE PROTEIN IS ALREADY FOLDING
AND THE OTHER FOLDING PROTEIN
WITH THE BAIT PROTEIN?
I'M NOT SURE I
ENTIRELY UNDERSTAND THE QUESTION.
I GUESS
I'LL SAY THAT IN MOST CASES, BOTH,
YOU KNOW, BOTH THE BOTH THE BAIT AND
AND THE PREY PROTEINS WILL FOLD,
YOU KNOW, BOTH THERMODYNAMICALLY
AS WELL AS WITH ALPHAFOLD ON THEIR OWN.
THERE ARE INSTANCES SO
SO THERE ARE INTRINSICALLY DISORDERED
REGIONS, AS EVERYONE KNOWS.
AND A LOT OF THESE CONTAIN
SHORT LINEAR MOTIFS, SHORT PEPTIDES
THAT ARE USUALLY HIGHLY CONSERVED
BUT EMBEDDED WITHIN OTHERWISE
DISORDERED REGIONS.
AND, WE OFTEN SEE
THAT THESE ARE UNFOLD
FOLDED ON THEIR OWN.
BUT WHEN WE FOLD THEM
WITH A FUNCTIONALLY RELEVANT PARTNER
THAT THEY NOW ADOPT, A HELICAL FOLD.
SO, SO THAT IS,
I THINK
PROBABLY THE MOST PROMINENT
SORT OF SITUATION IN WHICH THE, YOU KNOW,
THE, THE,
THE ACT OF ACTUALLY
BRINGING TWO PARTNERS TOGETHER
INDUCES FOLDING,
BUT OTHERWISE,
THAT THAT IS TYPICALLY NOT THE CASE.
BUT BUT I'M NOT SURE I ENTIRELY
UNDERSTOOD THE QUESTION, BUT I HOPE,
HOPEFULLY I GOT AT LEAST PART OF IT.
I'LL ASK THE NEXT ONE.
WEI YANG (HI WEI) ASKS
IS
STK19 IS PREDICTED TO INTERACT WITH MSH2
TO MUCH TO JUST BELOW CSA AND XPD
WHAT IS KNOWN OF
STK19 AND MISMATCH REPAIR?
NOTHING TO MY KNOWLEDGE.
AND,
I DON'T REMEMBER THE EXACT SPOC SCORE,
BUT I THINK
I THINK THERE WAS
A BIT OF A DROP OFF IN TERMS OF,
YOU KNOW, THE,
THE ACTUAL CONFIDENCE VALUE.
BUT, YOU KNOW,
IT'S POSSIBLE,
I DON'T THINK ANYBODY HAS LOOKED AT
WHETHER THERE IS A FUNCTIONAL INTERPLAY
OF STK19 WITH MISMATCH REPAIR.
AND THIS IS, YOU KNOW, THIS IS WHERE
THERE IS OBVIOUSLY OFTEN A GRAY ZONE,
WITH THIS STRUCTURES
PREDICTION BUSINESS, THE
I WOULD SAY THE MOST,
YOU KNOW, COMPELLING CASES ARE
WHEN YOU GET A PREDICTION
THAT REALLY GIVES YOU
A EUREKA MOMENT, RIGHT?
AS IN THE CASE OF STK19
INTERACTING WITH CSA AND XPD,
TWO FACTORS
ALREADY KNOWN TO BE IN THE SAME PATHWAY.
THAT'S THAT'S REALLY KIND OF A NO BRAINER
WHERE YOU
YOU LOOK AT THAT PREDICTION,
YOU SAY,
YOU KNOW THAT THAT IS
THAT MAKES SO MUCH SENSE
THAT I'M GOING TO SPEND
THE TIME IT TAKES TO TEST THIS IDEA.
IN OTHER INSTANCES, IT CAN BE
OBVIOUSLY A MUCH RISKIER PROPOSITION.
AND SO IN THE CASE OF STK
19 AND MISMATCH REPAIR, YOU KNOW, I CAN'T
I REALLY CAN'T COMMENT,
ON WHETHER THAT'S WORTH PURSUING OR NOT
OR WHETHER THERE'S ANY,
ANY PRIOR EVIDENCE.
WE CERTAINLY DON'T HAVE ANY.
OKAY.
THE NEXT QUESTION IS FROM DMITRI GORDENIN.
WOULD YOU,
WOULD YOUR PLASMID SYSTEM
BE APPLICABLE TO NON-BULKY
BASED LESIONS
IMPEDING RNA POLYMERASE?
RIGHT.
I THINK I THINK IN PRINCIPLE, YES.
AND IT'S
ACTUALLY BRINGS UP AN INTERESTING POINT,
WHICH IS THAT THERE ARE PRESUMABLY
THERE ARE
AND I'M SURE
THERE ARE PROBABLY OTHER PEOPLE
ON THE CALL
WHO KNOW MORE ABOUT THIS THAN I DO,
BUT THERE ARE PROBABLY LESIONS, SUCH
AS ABASIC SITES THAT WOULDN'T TRIGGER
THE GLOBAL GENOMIC REPAIR PATHWAY,
BUT THAT WOULD ABSOLUTELY STALL
RNA POLYMERASE.
BUT THEN I GUESS BUT THEN I GUESS
THE ISSUE IS
THAT THEY MAY NOT STALL THE XPD HELICASE.
SO, YEAH, IT'S AN INTERESTING QUESTION.
WE'VE NOT DONE ANYTHING BEYOND
USING THE CISPLATIN 1,3-G13
INTRA STRAND CROSS-LINKED.
BUT CERTAINLY
THE SYSTEM LENDS ITSELF TO EXPLORING
MORE WIDELY WHAT RANGE OF LESIONS
WOULD ACTUALLY LEAD TO PRODUCTIVE,
TECHNIQUE FOR.
OKAY.
DMITRI HAS A FOLLOW UP QUESTION
ON A COMPLETELY DIFFERENT TOPIC
HOW MUCH ALPHAFOLD BASED
PIPELINES ARE APPLICABLE
TO PREDICTION OF SNP EFFECTS PER SE?
WELL INTEGRATED
WITH EXISTING BIOINFORMATICS
PREDICTION METHODS, POLYPHEN, ETC..
RIGHT?
I THINK WELL,
I THINK THE UNDERLYING QUESTION HERE IS,
WHETHER YOU CAN USE ALPHAFOLD TO,
YOU KNOW, MODEL POINT MUTATIONS.
AND BY AND LARGE, ALPHAFOLD REALLY
IGNORES IF YOU.
SO IF YOU INTRODUCE, YOU KNOW,
A FEW MUTATIONS,
IN YOUR, YOUR BAIT OR YOUR PREY PROTEIN,
ALPHAFOLD WILL LARGELY IGNORE THAT.
AND THE REASON FOR THAT IS,
OF COURSE, THAT
WHAT IT DOES IS IT IT CONSIDERS,
YOU KNOW,
A WHOLE MULTIPLE SEQUENCE ALIGNMENT.
SO IT IT ALWAYS LOOKS FOR,
YOU KNOW, AS MANY,
ORTHOLOGS AS IT CAN,
AND THEN IT BUILDS,
YOU KNOW, MULTIPLE SEQUENCE ALIGNMENT.
IT LOOKS FOR, FOR COVARIATION.
AND SO IF, IF, IF YOU TWEAK ONE
PARTICULAR MEMBER OF THE MSA,
IT REALLY HAS NO EFFECT.
BUT OF COURSE THERE ARE
THERE ARE ALGORITHMS
THAT HAVE BEEN DEVELOPED
TO, ADDRESS THAT VERY THING.
AND ALPHA ALPHA MISSENSE IS PROBABLY,
YOU KNOW, THE BEST,
I THINK STILL RESOURCE TO ACTUALLY,
GET A SENSE OF WHETHER A MUTATION IS, IS
DELETERIOUS OR NEUTRAL.
NOW THE NEXT QUESTION IS FROM ROB SCOTT.
HELLO.
THANKS VERY MUCH FOR THE TALK.
AND,
HE'S WORKING IN, ALL ATOM
MOLECULAR DYNAMICS SIMULATION,
AND HE'S LOOKING FOR APPLICATION
IN DNA REPAIR.
AND HE ASK,
CAN YOU PLEASE TELL
IS THERE SOME PARTICULAR PROBLEM
SEE, YOU COULD RECOMMEND THAT
THAT HE WORK ON.
AND FOR AN ALL
ATOM SIMULATION.
GOSH.
WELL,
I MEAN, I THINK,
I THINK AS SOON AS YOU START TO MODEL,
YOU KNOW, NOT ONLY PROTEINS, BUT,
BUT OTHER, YOU KNOW, LIGANDS,
YOU HAVE TO START TO MOVE INTO AN ALL
ATOM, SORT OF SETTING.
AND OF COURSE,
THAT'S A LOT OF
WHAT ALPHAFOLD THREE IS DOING.
BUT I DON'T
I DON'T THINK I HAVE A REALLY GOOD
SPECIFIC, RECOMMENDATION FOR YOU.
I'M HAPPY TO CORRESPOND
WITH YOU OVER THAT. AND IF YOU WANT.
THERE'S A
QUESTION FROM
SOMEBODY THAT JUST LABELED
WOODGATES LAB.
I DON'T KNOW IF IT'S ROGER
OR SOMEBODY ELSE SAYING NICE.
NICE TALK AND DETAIL.
SMILEY FACE.
DID YOU CHECK THE CURRENT
ACTIVITY OF STK
19 IN THE COMPLEX,
OR IS IT ACTING MORE AS AN ADAPTER?
WELL, SO SO I CERTAINLY HAVE NOT
WE'VE NOT LOOKED AT, KINASE ACTIVITY,
BUT REALLY, I MEAN,
IT DOESN'T LOOK
LIKE ANYTHING LIKE A KINASE.
SO IT WOULD BE TRULY SHOCKING
IF IT HAD KINASE ACTIVITY.
BUT I THINK, YES,
ACTUALLY, PUBLISHED A PAPER
WHERE HE ADDRESSED
NOT ONLY THE MIS-
ANNOTATION OF STK19,
BUT ALSO,
YOU KNOW,
THE FACT THAT IT'S NOT A KINASE.
AND HE DID NOT LOOK AT IT
IN THE CONTEXT OF A COMPLEX,
BUT CERTAINLY IN ISOLATION,
AND FOUND NO EVIDENCE OF KINASE ACTIVITY.
AND IT WOULD BE VERY SHOCKING
IF IT SUDDENLY BECAME A KINASE,
WHEN IT WHEN IT BINDS TO THE TC-NER COMPLEX
AND WE HAVE A MESSAGE FROM, FROM,
ANDREW JACKSON
AND HE SAY, HI, YOHANNES IN SPOC
DID YOU LOOK AT,
WHICH PARAMETER GAVE MOST
PREDICTIVE VALUE?
IF SO, WHICH WERE MOST INFORMATIVE?
RIGHT. YEAH, THAT'S A GREAT QUESTION.
SO I'M TRYING TO REMEMBER
FROM THE STRUCTURAL FEATURES,
IT WAS ACTUALLY,
I BELIEVE IT WAS A METRIC
THAT WE CALL AVERAGE MODELS.
SO, SO ONE OF THE HOMEGROWN METRICS
THAT WE CAME UP WITH
WAS SIMPLY TO QUANTIFY THE AGREEMENT
AMONG THE FIVE INDEPENDENTLY
TRAINED ALPHAFOLD MODELS.
SO PROBABLY MANY OF YOU KNOW
THAT THAT ALPHAFOLD WAS TRAINED ON FIVE,
SLIGHTLY DIFFERENT, REGIMES.
AND SO WHEN YOU GIVE IT A PREDICTION
WHERE YOU GIVE IT A PROTEIN
OR A PROTEIN PAIR,
IT ACTUALLY SPITS OUT FIVE SOLUTIONS.
AND AND SO WHAT WE FOUND
WAS THAT THE GREATER
THE AGREEMENT
AMONG THOSE,
FIVE MODELS, THE MORE LIKELY
SOMETHING IS TO BE TRUE.
AND WE ACTUALLY HAVE
THAT AS A FEATURE IN SPOC.
SO, SO ON THE STRUCTURAL SIDE,
THAT IS ACTUALLY ONE OF THE BEST FEATURES
ON THE BIOLOGICAL SIDE, IT TURNS OUT
ACTUALLY TO BE BIOGRID.
SO AS YOU KNOW, BIOGRID,
YOU KNOW, IT CURATES
NOT ONLY THE LITERATURE BUT ALSO,
YOU KNOW, A LOT OF PROTEOMIC DATABASES
AND SO, PERHAPS NOT SURPRISINGLY, BIO
GRID IS IN FACT, THE MOST,
IMPORTANT METRIC ON THE BIOLOGICAL SIDE.
BUT IT IS BY NO MEANS IT IS BY NO MEANS,
YOU KNOW, SUFFICIENT.
AND, AND AND WE ACTUALLY SEE
MANY EXAMPLES OF PROTEIN PAIRS
LIKE STK19-XPD,
WHICH ARE NOT REPORTED IN BIOGRID.
THAT INTERACTION IS COMPLETELY UNKNOWN.
YET THEY SCORE SUPER HIGHLY.
SO SO, YOU KNOW, IT'S A COMPLEX
IT'S A COMPLEX PICTURE.
SO, YOU KNOW, THE CRISPR SCREENS AND,
YOU KNOW,
CO-EXPRESSION
ALL OF THOSE THINGS CONTRIBUTE.
AND SO
AND SO IT'S
REALLY A SUM OF MANY PARTS
THAT GIVES YOU THE,
THE ULTIMATE PERFORMANCE.
THAT IS SPOC.
OKAY.
ROB SCOTT JUST SAYS THANKS.
HE WAS GUY
WITH THE QUESTION
ABOUT WHAT PROBLEMS TO WORK ON.
MAYBE THIS IS SOMETHING YOU COULD FOLLOW
UP, OFFLINE, BUT KEN WANTS TO ANSWER
ASK A QUESTION KEN.
WHAT A WONDERFUL PRESENTATION.
I REALLY ENJOYED THAT.
IF SDK19 IS INVOLVED IN
DNA REPAIR AND TRANSCRIPTION
COUPLED REPAIR.
AND WE KNOW THAT THE
MUTATIONS IN THAT, CAUSE HUMAN DISEASES
ARE, THE TRANSCRIPTION COUPLED REPAIR
ABNORMALITIES SEEM TO INVOLVE
MORE NEUROLOGIC DEGENERATION
RATHER THAN CANCER.
I HAVE YOU BEEN ABLE
TO LOOK AT ANY OF THESE NEW LARGE
GENOME DATABASES
TO SEE IF THERE ARE
ANY ABNORMALITIES IN STK
19 THAT READ HUMAN DISEASE OR TO CATCH.
YEAH. THAT'S A IT'S A TERRIFIC QUESTION.
PERSONALLY WE'VE NOT DONE THAT.
I BET,
I BET SOME OF THE OTHER GROUPS
WORKING ON STK19 THAT ARE MORE
GENETICALLY ORIENTED THAN WE ARE,
HAVE PROBABLY DONE THAT.
AND I IMAGINE
THAT THE ABSENCE OF, OF ANY,
STATEMENTS OR REPORTS IN, IN ANY OF THE,
PAPERS,
SUGGESTS THAT SO FAR AT LEAST,
THERE ARE NO PATIENT MUTATIONS.
AND I NOW REALIZE THAT I,
I THINK I MAY HAVE ACTUALLY,
NEGLECTED TO MENTION THE OTHER GROUPS.
I THINK I HAD THEIR,
THEIR REFERENCES ON MY SLIDE,
BUT I DO WANT TO POINT OUT THAT,
I THINK IT'S
THREE OTHER GROUPS ALSO REPORTED
THE ROLE OF STK19 IN TC-NER
AND, AND A NUMBER OF THOSE,
ALSO PROVIDED EVIDENCE
FOR THE INTERACTION WITH XPD,
IN ALL CASES BASED ON
THE ALPHAFOLD PREDICTION.
I DON'T SEE ADDITIONAL QUESTIONS.
SO I THINK WE'LL JUST, STOP HERE
AND I WOULD LIKE TO TAKE THIS OPPORTUNITY
TO THANK DOCTOR WALTER
FOR SUCH A FASCINATING
AND INSIGHTFUL PRESENTATION
AND THE GROUNDBREAKING WORK THAT
CLEARLY ADVANCED
UNDERSTANDING FOR TRANSCRIPTION
COUPLED WITH DNA REPAIR.
I WOULD ALSO LIKE TO THANK EVERYONE
FOR JOINING
TODAY'S SESSION AND THANK YOU ALL.
AND WE ARE LOOKING FORWARD
TO SEE YOU IN THE FUTURE EVENTS.
THANK YOU. HAVE A GREAT DAY.
THANK YOU, DOCTOR WALTER.
YEAH, THANK YOU ALL FOR LISTENING.
YEAH. BYE BYE.