InSilico

I have a more specific question. I've found what appears to be a technical issue in the commercial potential of stem cell therapy: patient-specificity vs. patient-independence. To be more precise, from what I've read, successful induced pluripotent stem cell (iPSC) differentiation and application appears to still be patient-specific. That is: only cells from a single patient can be used effectively as a therapy for that patient. First, I'd like to know if anyone has reason to believe otherwise? If so, could you cite a (recent) article explaining where I've missed something? Are there patient-independent iPSC methods currently in practice? If my understand is correct, could anyone venture a thought as to if or how this might be overcome? Is there research being done to address the patient-specificity?

I've been tasked with a relatively interesting assignment: a review manuscript on the biotechnological applications of adipose-derived stem cells (ASCs). I've gathered a fair number of articles discussing how ASCs (which I understand are mesenchymal stem cells, MSCs) can be extracted from human adipose tissue and made to differentiate into at least three different varieties of tissue. One paper clarifies methods for inducing differentiation into three different tissues specifically: bone, cartilage and adipose tissue. I suppose I'm off to a good start. Still, the story doesn't end there. I'm looking for the challenges that ASCs face, particularly technical challenges. I understand that stem cells in general face a number of ethical challenges, some of which I presume permeate the notion of using them for industrial (which is to say: business) applications. Is it true that human tissue cannot be sold? How would a business looking to provide stem cell therapy overcome this? Unless legislation changes, would they be able to? I should note, though, that I'm interested more directly in some of the technical challenges that stem cells still face. Obviously, it's a new and growing field of study, and there's still much to be understood. I'm wondering how efficiently one is able to identify, extract, isolate, purify, induce differentiation and ultimately employ stem cells in a meaningful (or potentially meaningful) way? From the literature I've read, it seems as though many of the differentiation methods have been sort of one-off experiments that met with success, in the sea of unsuccessful attempts. Is there enough consistency in any one method of differentiation that could lead to business applications? If not, why not? If not, what sort of research could be done to overcome it? I realize that I'm asking some very open-ended questions, the answers to which may not be published by any peer-reviewed journal, but I'd appreciate any feedback you'd be willing to offer. Of course, I'm desperately hungry for citations, so if you're aware of any relevant journal manuscripts, even reviews, I'd honestly love to read them. Please do bring them up. Thanks again everyone. I look forward to hearing what y'all think.

Lehninger 4 life, yo. Alternatively, I found an old text (actually recommended to me by my mother who found it - along with Lehninger, of course - useful when she was getting her PhD in biochem) pretty handy: Biochemistry: a Problem's Approach by W.B. Wood. http://www.amazon.com/Biochemistry-Problems-Approach-W-Wood/dp/0805398406

The notion that there haven't been big advances in the understanding of complex molecular interaction is a excuse for a lack of progress in the computational drug design world, and it's something I figured was the case, but wasn't able to find any real citations to uphold it. Can anyone else confirm (conclusively) that this is really the cause for the holdup? Oh? Sounds neat. What all do you study?

Could you clarify what you mean by the "DNA codon process"?

Sounds like an awesome opportunity. If you don't mind my asking, what's your education level? Is this a college-level project? How extensive is your experience in the microbiology field? There's a lot of really neat stuff to explore in the realm of biotech related to microbiology. A few that come to mind relate to things like bioremediation (the removal of pollutants from an environment using microbes with specific metabolic preferences), and biofuels (ethanol production from lignocellulosic biomasses, or algal production of hydrocarbons [bio-diesels]), as well as some potentially fun stuff like beer brewing (again looking to EtOH production). If none of those stand out to you and you're looking less for something with industrial applications, consider exploring stuff that's taking place relative to the human microbiome. It's definitely neat stuff. It seems to me that one of the biggest factors in determining your project is quite what interests you most. After that, figuring out quite what level you can operate at in terms of experimentation (what sort of supplies and equipment you have access to, as well as your understanding and familiarity of the techniques requires, and ultimately how much time/effort you're willing/able to put into this bad boy) can focus your options a bit further. So what sounds like fun to you?

I've recently developed a fascination in bioinformatics. The idea of using in silico models for things like hit and lead identification, screening millions of compounds for similarity in shape or pharmacophoric activity to discover a handful that might have potential for further tests (in vitro and in vivo) - it's something that I see as having an enormous potential. Of course, the applications of bioinformatic tools don't end with lead identification. Theoretically, one might be able to use digital simulations to test for alternative interactions between the lead compound (drug candidate) and other, non-intended (non-target) endogenous sites (proteins, DNAs, RNAs, for example). This, then, might be useful in lead optimization, where you'd then have to manipulate the compound in order to increase specificity and decrease toxicity. So you understand that I think this is a cool set of concepts. The notions here excite me, but I'm really interested in learning more. As much more as I possibly can. I realize that the things I've described above are conjecture based on ideal databases and ideal tools which may either not (yet) exist or may not be available to anyone but their developers. I'm wondering, though, quite how deep this rabbit hole goes and what I can learn. If you have any background in the field, or maybe if you know somebody who does, you'd be doing me a tremendous service in helping me expand my understanding of the role of bioinformatics in the drug discovery and drug development process. I've been told that these notions have existed for decades; that the concept of in silico screening in drug discovery has existed for a long time now and hasn't changed much. I don't know what to make of that claim. Is it true? If no significant advances have been made in the last, say, 5 years, why not? With the advances in computing power, I would imagine that the field of bioinformatics would be evolving in direct relation. Also, can anyone identify an instance of successful drug design (that is, a pharmaceutical that was demonstrated as effective and/or marketable) that relied on bioinformatic screening techniques? Is there a drug out there that was designed from such a rational approach? I'd love to get some real-world examples I can explore further. I want to say finally that I appreciate a community like this and all of you who enable it. I've been a member here in the past (under a different email and username which I'm afraid I've since forgotten), and I regret having been away for so long. I hope to generate meaningful discussions now that I'm back. I'm looking forward to getting to know you all, again. Thanks in advance for your input.