|
ool.weizmann.ac.il
|
Answered by Doron Lancet
The idea is actually a set of ideas.
They evolved over the last 6 years. The see d was a model developed for molecular
recognition, called the Receptor Affinity Distribu tion Model (RAD) (see Lancet, D.,
Sadovsky, E. and Seidemann, E. (1993). Probability model for molecular recognition in
biological receptor repertoires: significance to the ol factory system. Proc. Natl. Acad.
Sci. USA 90: 3715-3719). RAD is applicable to the unde rstanding of the interaction between
receptor repertoires and and multitude s of ligands, as in the olfactory system (my last 20
years science romance) and the immune system (my Ph D topic in the 70's).
Like so many scientists I was generally interested in this profound scientific/p
hilosophical question of the Origin of Life, but did nothing about it. I became more
seriousl y involved when beginning to attend the yearly meetings of the Israel Society for
t he Orig in of Life (ILSOL) headed by Prof. Noam Lahav from the Hebrew University.
Somewhere in 1994
I had this sudden insight that the RAD model was applicable to a specific appro ach to the
origin of life - that of mutually catalytic networks (Stuart Kauffman from Santa fe) and h
omeostatic quasi-steady states (Freeman Dyson from Princeton). I became an intellectual fan
of these no-RNA no-DNA models (Dyson calls them the "Garbage Bag" models in the recent ed
ition of his classical book "Origins of life (2nd Ed Cambridge U. Press). We then develop
ed an entire formal, thermodynamically rigorous framework for an Origin of life scenar io
that may be simulated on supercomputers (the Graded Autocatalysis Replication Domain (GARD)
model.
The final touch, explaining "why lipids" was through studying the papers of Luig i Luisi,
which describe replicating lipid vesicles. This is elegant because lipids can sp
ontaneously form supramolecular structures - micelles and vesicles. What was missing in
Luisi's treatise was storable, transmittable information, which Luisi has added
in in the form of RNA within the lipid vesicles. I developed the idea that lipids themselv
es could store information, not through sequences but through compositions. This go t mer
ged with the GARD model to provide a complete, self consistent novel scenario for the ver y
early steps in the process that led to the appearance of life - "The Lipid World". The
model has the best of all worlds: assemblies form spontaneously, contain compositional inf
ormation, undergo evolution-like changes through forming mutually catalytic networks, and
are capable of undergoing a process akin to self replication through a simple splitting
proc ess that lipid assemblies are known to be capable of.
Please bear in mind that very little is in the way of hand-waving, and most of it stems
from rigorous and provable principles of biophysics and chemistry. We claim that
we may have found the long-sought bridge between the inanimate world and a living cell.
This has been elaborated on by many researchers, e.g. Robert
Shapiro from NYU se e Shapiro, R. (1986). Origins: A skeptic's guide to the creation of
life on Earth.
N.Y., Simon & Schuster, Inc. The major obstacles: a) ANY covalent polymerization is
thermodynamically unfavorable, and will occur very sluggishly if at all under pr ebiotic
conditions. Non covalent assembly formation is much more likely. b) for an hone st to god
RNA or DNA to form, one needs to string together very few types of very special monomers -
nucleotides or similar. The prebiotic world likely was much more like a huge, pl anet scale
random chemistry experiment, where millions of different types of monomers would
be present. These will continuously disturb the process of forming the "purist" A,T ,G,C
RNA/DNA polymers. Rather, a terribly messy polymer, often branched in crazy ways rather
than linear as RNA is, and containing lots of monomers that would never be capable of the
orderly, wonderful process of base-pairing and mutual complementarity c) RNA/DNA as present
in today's cells are DEAD, and cannot self replicate ,except with the he lp of a complex
enzymatic machinery. Thus, the idea that early on RNA was the first self-replicating entity
is very tenuous. There is a chicken an egg problem that moist scientists agree on: you need
long, complex RNA to code for proteins and protein s to allow such RNA to make its own
copies. None could spring into existence without the ot her, and it is very difficult to
see both arising simultaneously.
This is the topic of our next
papers. We foresee a slow, graded takeover, in whi ch, driven by the rudimentary capacity
of lipid GARD assemblies to replicate and evolve, ch emical selection will favor a small
subset of monomers, PRIOR to any polymerization. N ext, very short polymers would
gradually form, inside the GARD assemblies, and driven by t he vey high local concentration
of monomers (dilution is one of polymerization's problems). All this will happen within an
already existing mutually catalytic network, which as can be shown mathematically, will
favor some reactions and abolish others. This gradual passa ge from a very primitive
network with monomers only to ones with longer and longer polymer s may in fact be the
solution to the Chicken & Egg problem. But the major answer to this question - we still
have to work hard to find out how this happened. But, there is consolat ion in claiming
that RNA and DNA are the RESULTS of an evolutionary process rather than
is prerequisites.
Very likely in a watery environment, but minerals
from rocks may have been cruci al.
Experimental proof may take
football filed size "test tubes" and time scales of years (if not decades or centuries) of
careful watching, entailing sophisticated nano-analysis we don't yet have today. Most
likely the proof will come in the world of "in-silico" chemist ry and biology, huge
supercomputer simulations. This is legitimate - after all very pro minent fields of
research such as the Origin of the Universe, galaxy formation, planet accretion, super
novae and black holes are studied by such means. Why not the origin of lif e - a one time
event (for all we know), that may have taken millions of years, and may be utterly
difficult to imitate in any size test tube, but with 2020-style computers could be looked
at in utter detail and rigor.