I've been wanting for a while to prepare something rigorous to develop this idea. Since I've simply not found the opportunity to do so, and I don't at the moment foresee when a good block of time in the near future will open for this to happen, and since one never knows what tomorrow will bring, I wanted to present the idea in a crude fashion.
As yet, while scientists appear to be homing in on the necessary conditions for the origins of life, the actual physical mechanism that generates life from inanimate matter still appears to be elusive. Some recent discussions:
Until actual life is generated from a bunch of inanimate molecules, it is safe to say that none of the proposed processes are proven to represent an actual origin of life.
So, since it is still an open question, in a very crude form, I suggest a possible contributing mechanism. Although my paper "The peloton superorganism and protocooperative behavior" (1), and our other papers (2-3) set out the mechanism I refer to here, these papers do not suggest how the principles might apply to origin-of-life mechanisms. This is a first sketch of such an application.
I have also written blog posts with similar videos to the one below, but this one is made with the specific purpose of demonstrating a simple possible mechanism for life to emerge from a collection of otherwise inanimate molecules. The video is poor quality, and the simulation platform doesn't allow an applet to be generated, but the simulation itself is what is important..
In the simulation, the circles or balls represent a collection of molecules. It is assumed that the appropriate molecules have aggregated in our primordial soup, so I need not name them.
The appropriate energetic source for the process proposed is more likely to be a thermal vent of some kind, since the collection of molecules is driven by a constant energetic source to aggregate, divide, and re-aggregate.
The aggregation and division process here is facilitated in part by an energy saving mechanism that allows larger aggregates to move through the heated liquid medium faster than smaller aggregates. Although not by any means conclusive, this short simulation is constructed with the same basic principles as in papers (1-3), and the process of larger groups moving faster than smaller ones is somewhat indicated in the video.
Whether such an energy saving mechanism is present among moving molecule aggregates, is not something I have researched at this point, and hence why this is a crude beginning. However, it is known that drafting occurs among comparatively small particles in a liquid medium (4), so I suggest it is not far-fetched that a drafting-like mechanism may be present among molecule aggregates, and certainly worth investigating further.
In the video, the molecules are first in aggregate motion under a comparatively low energetic input. However, we can reconfigure the group of molecules by driving them with higher energetic output, which may sort them into groups of different molecular size. In the simulation, the molecules are the same physical size, but they have their own intrinsic "output capacity" which is equivalent to size.
This hypothesized sorting process would occur because larger molecules would permit greater drafting opportunities: below a critical threshold, smaller particles can stick with larger ones at the same energetic input by virtue of drafting which equalizes differences in energetic capacity (internally or externally driven), but above that threshold, they are driven to separate, and may tend to group by size. This is a process we have modelled in (1-3), and (4) provides some indication of how this might work for small particles in water. More work would certainly need to be done to demonstrate the process under true molecular conditions.
Nonetheless in this simplified model, in our thermal vent, the sorting processes would be fairly continuous in view of temperature fluctuations in the vent and due to re-positioning of molecule aggregates across cooler and hotter vent regions. Thus there would be ongoing group reintegration and division.
The simulation also demonstrates the presence of a continual convective motion on the peripheries of the molecule aggregates. This is fairly easy to see with the naked eye, although below I show a plot from (1) that indicates this process. Further data and analysis are obviously required to demonstrate this. This convective motion represents a mechanism for the formation of protocell membranes. This convective process is largely generated by the coupling mechanism of drafting; molecules rotate on peripheries as internal molecules are less free to advance positions. Thus protocells are generated which re-integrate and divide. Under this continual process, eventually they sort into the appropriate configuration to generate RNA and/or DNA structures. If a sufficient number emerge at the same time, this continuing process of reintegration and and division sets in motion the evolutionary process.
This is what this short video demonstrates:
It is worth noting that a convective dynamic traces a sinusoidal trajectory on a two-dimensional plot. This translates in 3-dimensions to a helical motion as the aggregate moves forward in space. A double convective motion (i.e. rotations forward on both peripheries and falling backward down the middle) produces a double-helical pattern as the aggregate moves forward in space. Below is Figure 8 from (1). It shows a division and re-integration dynamic among 50 agents (simulated cyclists in this case). The black circles show group divisions, and the red circles show re-integrations. We can see approximately sinusoidal trajectories among the cyclists as they rotate from the back of the group to the front, and back again. Much the same dynamic is occurring in the video above.
How this process might solidify or become fixed into a helical structure is unknown, but we can hypothesize that the noted temperature changes in the liquid medium may be involved.
1.Trenchard, H., 2015. The peloton superorganism and protocooperative behavior. Applied Mathematics and Computation, 270(C), pp.179-192.
- 2. A deceleration model for bicycle peloton dynamics and group sorting, Hugh Trenchard, Erick Ratamero, Ashlin Richardson, and Matjaž Perc, Appl. Math. Comput. 251, 24-34 (2015)
- 3. Collective behavior and the identification of phases in bicycle pelotons, Hugh Trenchard, Ashlin Richardson, Erick Ratamero, and Matjaž Perc, Physica A 405, 92-103 (2014)
4. Wang, L., Guo, Z.L. and Mi, J.C., 2014. Drafting, kissing and tumbling process of two particles with different sizes. Computers & Fluids, 96, pp.20-34.