Protein Design: Automated protein discovery and synthesisWritten by Paras Chopra
In this paper I describe (theoretically) method(s) of automated protein discovery and synthesis. 1. Protein Folding Problem To solve protein folding problem we can use Artificial Neural Networks. We will train networks with natural proteins whose 3D structure and amino acid sequence is known. After that we will test network with few new artificially designed proteins to check if it works correctly. If it doesn't, we will be changing some of network's parameter such as training iterations, no of hidden layers, etc. And train network again. To check protein's 3D structure, we need to have a model of actual physical world in computer model. 2. Simulation of Physical World This is trickiest part. To simulate physical world at atomic level is very difficult. We need to take into account: covalent bonds, spatial & temporal parameters, weak interactions such as hydrogen bonds, dipole interactions, etc. We also need to simulate chemical reactions. This will probably require huge amounts of computing power. Or perhaps, neural networks can be employed here also as little inaccuracy produced by a neural network can take care of randomness at quantum level. The neural networks will be used to predict/calculate magnitude of effect of various forces on an atom/molecule and also how these behave at a grander inter-molecular level. 3. Designing Proteins To design proteins, we will be using Genetic Algorithm method. The random amino-acid sequences will be evolved & tested by converting these sequences into their respective 3D shape by trained neural network. The best sequences will be retained, while other mutated or crossed-over, etc. The fitness function will work in simulated physical world. If protein produced is successful in carrying out our desired unction, then it is fit else it is not. Actually we will assign a fitness level from 0 to 100. Once final amino acid sequence is determined, it will be sent to Protein Printer.
| | Memory Research Misses The ObviousWritten by Abraham Thomas
The search to reveal a mystery. Research laboratories around world sought location of human memory. The research had followed diverse leads. One clue related to branched inputs of nerve cells, called dendrites. Branch growth was assisted by a protein called cypin. Some memory disabilities were related to deficits in cypin. So, one possibility was that nerve cells grew new branches to store memory. New branches could represent added memory. But, human memory was immense. People were reported to be able to recognize, with 99.5% accuracy, any one of 2,500 images shown to them at one second intervals. Each of those images contained millions of pixels of specific information. When size and scale of human memory was considered, idea of branches, however microscopic, growing to add memories sounded perilously cancerous. More hints. LTP was another possibility. High frequency stimulation of dendrites of a neuron were known to improve sensitivity of synaptic nerve junctions. Such activity was seen to be "remembered" by cell through greater sensitivity at specific inputs. Neurochemicals at synaptic junctions were also known to increase such sensitivity. But, while process enhanced memory, LTP failed to offer a global hypothesis about how memory could be stored. Without answers. The hippocampus was also mentioned in connection with memory research. Damage to this organ, a component of a region of brain called limbic system, was known to cause patients to forget ongoing events within a few seconds. But, incidents from childhood and early adult life were still remembered. Memory had faded from a couple of years prior to event that caused damage to hippocampus. Older memories were still retained by patient even without hippocampus. Evidently, organ did not store such memories. It could play a role, but actual storage of memory remained enigmatic. In end, all science did know was that memory resided all over system and that one particular organ helped formation of memories. Combinatorial coding. Yet, answer to memory enigma had been staring them in face for years. That happened, when science acknowledged use of combinatorial coding by nerve cells in olfactory system. Combinatorial coding sounded confusing and complex. But, in context of nerve cells, combinatorial coding only meant that a nerve cell recognized combinations. If a nerve cell had dendritic inputs, identified as A, B, C and so on to Z, it could then fire, when it received inputs at ABD, ABP, or XYZ. It recognized those combinations. ABD, ABP, or XYZ. The cell could identify ABD from ABP. Subtle differences. Such codes were extensively used by nature. The four "letters" in genetic code – A, C, G and T – were used in combinations for creation of a nearly infinite number of genetic sequences. Highly developed skill. It was combinatorial coding, which enabled nerve cells of reptilian nosebrains to recognize smells and make crucial life decisions since beginnings of history. Such sensory power had been developed in animals to a remarkable degree. Research showed that dogs could register parameters of a smell and then pick it out from millions of competing smells. The animals could detect a human scent on a glass slide that had been lightly fingerprinted and left outdoors for as much as two weeks. They could quickly sniff a few footprints of a person and determine accurately which way person was walking. The animal's nose could detect relative odor strength difference between footprints only a few feet apart, to determine direction of a trail. Recording and recognizing ABD and DEF enabled animals to record and recall a single smell to differentiate it from millions of other smells. Inherited memories of millions of smells decided whether food was edible, or inedible, or whether a spoor was life threatening. The system had both newly recorded and inherited memories, which enabled them to recognize smells in environment. Inherited and acquired memories. While such remarkable odor recognition skills were known for ages, it was only in late nineties that science discovered combinatorial coding. A Nobel Prize was awarded for discovery of use combinatorial coding by olfactory system in 2004. The olfactory system used coding to enable a relatively small number of olfactory receptors to recognize different odors. Science discovered that particular combinations could fire to trigger recognition. In experiment scientists reported that even slight changes in chemical structure activated different combinations of receptors. Thus, octanol smelled like oranges, but similar compound octanoic acid smelled like sweat. We remembered smell of oranges. Even smell of sweat. Which meant that system remembered those combinations. But science failed to recognize true significance of combinatorial coding when they searched for location of human memory. Millions of combinations were possible for nerve cell with inputs from A to Z. But nerve cells had thousands of inputs. If nerve cells remembered combinations, then that could be location of a galactic nervous system memory.
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