Biological complexity: finding working proteins (Introduction)

by David Turell , Thursday, July 30, 2015, 01:36 (3405 days ago) @ David Turell

To make a new animal one much find workable proteins that will function in a meaningful way in cooperation with other proteins to give life. this article shows how enormous the odds are if one starts from scratch. This is why the Cambrian is so startling if viewed from a Darwin standpoint:- http://p2c.com/students/blogs/kirk-durston/2015/07/computing-best-case-probability-prot... life requires thousands of different protein families, about 70% of which are ‘globular' proteins, each with a 3-dimensional shape that is unique to each family of proteins. An example is shown in the picture at the top of this post. This 3D shape is necessary for a particular biological function and is determined by the sequence of the different amino acids that make up that protein. In other words, it is not biology that determines the shape, but physics. Sequences that produce stable, functional 3D structures are so rare that scientists today do not attempt to find them using random sequence libraries. Instead, they use information they have obtained from reverse-engineering biological proteins to intelligently design artificial proteins.
"What are the implications of these results, obtained from actual data, for the fundamental prediction of neo-Darwinian theory mentioned above? If we assume 10^30 life forms with a fast replication rate of 30 minutes and a huge genome with a very high mutation rate over a period of 10 billion years, an extreme upper limit for the total number of mutations for all of life's history would be around 10^43. Unfortunately, a protein domain such as Ribosomal S7 would require a minimum average of 10^100 trials. In other words, the sum total of mutational events for the entire theoretical history of life falls short by at least 57 orders of magnitude from what would have a reasonable expectation of 'finding' any RS7 sequence - and this is only for one domain. Forget about ‘finding' an average sized protein, not to mention thousands.-"I downloaded 3,751 aligned sequences for the Ribosomal S7 domain, part of a universal protein essential for all life. When the data was run through the program, it revealed that the lower limit for the amount of functional information required to code for this domain is 332 Fits (Functional Bits). The extreme upper limit for the number of sequences that might be functional for this domain is around 10^92. In a single trial, the probability of obtaining a sequence that would be functional for the Ribosomal S7 domain is 1 chance in 10^100 … and this is only for a 148 amino acid structural domain, much smaller than an average protein. (my bold)-***-"As we all know from probabilities, one can get lucky once, but not thousands of times. This definitively falsifies the fundamental prediction of Darwinian theory that evolutionary processes can ‘find' functional protein families. A theory that has an essential prediction thoroughly falsified by the data should have no place in science.-"Could natural selection come to the rescue? As we know from genetic algorithms, an evolutionary ‘search' will only work for hill-climbing problems, not for ‘needle-in-a-haystack' problems. There are small proteins that require such low levels of functional information to perform simple binding tasks, that they form a nice hill-climbing problem that can be easily located in a search. This is not the case, however, for the vast majority of protein families. As real data shows, the probability of finding a functional sequence for one average protein family is so low, there is virtually zero chance of obtaining it anywhere in this universe over its entire history - never mind finding thousands of protein families."-Comment: Note the reference to the need for understanding the information required.