Zero Probability is Not a Problempaper published in the Journal of Theoretical Biology, Hubert Yockey used information theory to evaluate the likelihood of the evolution of a relatively simple protein. Yockey’s model system was cytochrome c, a protein consisting of about one hundred amino acids. Cytochrome c plays an important role in the mitochondria’s electron transport chain (ETC) which helps to convert the chemical energy in carbon-carbon and carbon-hydrogen bonds, in the food we eat, to an electrochemical potential energy in the form of hydrogen ions (or protons) stored within the mitochondria’s inner membrane. Like water pressing against a dam and turning its turbines to generate electricity, the high-concentration hydrogen ions drive the ATP synthase “turbine” to create the high-energy ATP molecule. Like the electrical outlets in your house, the ATP molecule provides a standardized form of energy that is used for a wide range of applications in your body, such as muscle contraction and nerve signals. There is no scientific explanation for how the ETC evolved. There also is no scientific explanation for how a single protein, such as cytochrome c, evolved. Yockey explained this in 1977, and since then the problem has only gotten worse.
Given 20 different amino acids to choose from, then for a protein with a sequence of 101 amino acids, such as cytochrome c, there are 20 raised to the power of 101, or 20^101, different possible amino acid sequences. That represents an astronomically (and impossible) number of sequences for evolution to search through to find a functional cytochrome c protein.
The problem is more complicated than this, however, since the different amino acids are not equally likely and there are many different sequences that will form a functional cytochrome c protein.
Yockey accounts for these factors to determine the effective number of sequences evolution would have to search through to find cytochrome c. For instance, Yockey uses the known cytochrome c proteins at the time, from many different species, to get an idea of the different amino acids that are possible at each position, within the sequence of 101 residues. Some residues allow for quite a few different amino acids while others seem to be more stringent.
This approach is reasonable, but by no means the only way of estimating the number of different amino acid sequences that could work. One way or another, the bottom line is this: while the number of different sequences that could form a successful type of protein, such as cytochrome c, is a pretty big number, it doesn’t solve the problem.
Yockey found that the probability of evolution finding the cytochrome c protein sequence is about one in 10^64. That is a one followed by 64 zeros—an astronomically large number. He concluded in the peer-reviewed paper that the belief that proteins appeared spontaneously “is based on faith.”
Indeed, Yockey’s early findings are in line with, though a bit more conservative than, later findings. A 1990 study of a small, simple protein found that 10^63 attempts would be required for evolution to find the protein.
A 2004 study found that 10^64 to 10^77 attempts are required, and a 2006 study concluded that 10^70 attempts would be required.
These requirements dwarf the resources evolution has at its disposal. Even evolutionists have had to admit that evolution could only have a maximum of 10^43 such experiments. It is important to understand how tiny this number is compared to 10^70. 10^43 is not more than half of 10^70. It is not even close to half. 10^43 is an astronomically tiny sliver of 10^70.
Furthermore, the estimate of 10^43 is, itself, entirely unrealistic. For instance, it assumes the entire history of the Earth is available, rather than the limited time window that evolution actually would have had. And it assumes the pre existence of bacteria and, yes, proteins. In fact, the evolutionists assumed the earth was covered with bacteria, and each bacteria was full of proteins. That of course is not an appropriate assumption for the question of how proteins could have evolved in the first place. In fact, it is circular.
Of course the evolution of a single protein is only one of many problems for evolution. Consider, for example, the cellular apparatus that constructs proteins—the protein synthesis machinery. One paper used a back-of-the-envelope, simple and conservative calculation to show that the probability of such an apparatus evolving by chance is one in 10^1018. That’s a one followed by 1,018 zeros. Normally in science this would be considered far beyond impossible, so therefore evolutionists are considering an infinite universe, or multiverse, to solve the problem. In such a universe, it does not matter how improbable any event is, it will eventually occur:
Origin of life is a chicken and egg problem: for biological evolution that is governed, primarily, by natural selection, to take off, efficient systems for replication and translation are required, but even barebones cores of these systems appear to be products of extensive selection. The currently favored (partial) solution is an RNA world without proteins in which replication is catalyzed by ribozymes and which serves as the cradle for the translation system. However, the RNA world faces its own hard problems as ribozyme-catalyzed RNA replication remains a hypothesis and the selective pressures behind the origin of translation remain mysterious. Eternal inflation offers a viable alternative that is untenable in a finite universe … In an infinite universe (multiverse), emergence of highly complex systems by chance is inevitable. Therefore, under this cosmology, an entity as complex as a coupled translation-replication system should be considered a viable breakthrough stage for the onset of biological evolution.
There you have it. Probabilities don’t matter. You can point out how unlikely evolution is, and evolution remains a fact. Science is done by people, and people seek certain answers, regardless of the data.
Religion drives science, and it matters.