The Cradle of Gordon Life Science Institute and Its Development and Driving Force

Gordon Life Science Institute is the first Internet Research Institute ever established in the world. It is a non-profit institute. Those scientists who are really dedicated themselves to science and loving science more than anything else can become its member. In the friendly door-opened Institute, they can maximize their time and energy to engage in their scientific creativity. They have also believed that science would be more truthful and wonderful if scientists do not have to spend a lot of time on funding application, and that great scientific findings and creations in history were often made by those who were least supported or funded but driven by interesting imagination and curiosity. Recollected in this minireview is its establishing and developing processes, as well as its philosophy and accomplishments.

who has proved his/her creativity in science can become a member regardless of his/her age, occupation, and nationality. Accordingly, the Institute has provided an ideal society or organization for those scientists who are really dedicated themselves to science and loving science more than anything else. In the friendly door-opened Institute, these scientists can maximize their time and energy to engage in their scientific creativity. Members of the Institute believe science would be more truthful and wonderful if scientists do not have to spend a lot of time on funding application. We also note that great scientific findings and creations in history were often made by those who were least supported or funded but driven by intriguing imagination and awesome curiosity.

Extension of Special PseAAC to the General One
With the explosive growth of biological sequences in the postgenomic era, one of the most challenging problems in computational biology is how to express a biological sequence with a discrete model or a vector, yet still keep considerable sequence-order information or key pattern characteristic. This is because all the existing machine-learning algorithms (such as "Optimization" algorithm [1], "Covariance Discriminant" or "CD" algorithm [2,3], "Nearest Neighbor" or "NN" algorithm [4], and "Support Vector Machine" or "SVM" algorithm [4,5]) can only handle vectors as elaborated in a comprehensive review [6]. However, a vector defined in a discrete model may completely lose all the sequence-pattern information.
To avoid completely losing the sequence-pattern information for proteins, the pseudo amino acid composition [7] or PseAAC

Distorted Key Theory for Peptide Drugs
According to Fisher's "lock and key" model [293], Koshland's "induced fit" theory [293], and the "rack mechanism" [294], the prerequisite condition for a peptide to be cleaved by the diseasecausing enzyme is a good fit and tightly binding with the enzyme's active site (Figure1). However, such a peptide, after a modification on its scissile bond with some simple chemical procedure, will no longer be cleavable by the enzyme but it can still tightly bind to its active site. A schematic illustration about the distorted key theory is given in Figure 2, where panel   Shows an effective binding of a cleavable peptide to the active site of a disease-causing enzyme, while panel (b) The same peptide has become a non-cleavable one after its scissile bond is modified although it can still bind to the active site. Such a modified peptide, or ''distorted key", will automatically become an inhibitor candidate against the disease-causing enzyme. Adapted from [296] with permission.
Such a modified peptide, or ''distorted key", will automatically become an inhibitor candidate against HIV protease. Even for nonpeptide inhibitors, the information derived from the cleavable peptides can also provide useful insights about the key binding groups and fitting conformation in the sense of microenvironment.
Besides, peptide drugs usually have no toxicity in vivo under the physiological concentration [295]. For more discussion about the distorted key theory, see a comprehensive review paper [296]. It was based on such a distorted key theory that many investigators were enthusiastic to develop various methods for predicting the protein cleavage sites by disease-causing enzymes (see, e.g., [295,[297][298][299][300][301][302]). Furthermore, a webserver called "HIVcleave" [299] has been established for predicting HIV protease cleavage sites in proteins. Its website address is at http://chou.med.harvard.edu/ bioinf/HIV/. For more discussions about the "distorted key theory", see an insightful Wikipedia article at https://en.wikipedia.org/ wiki/Chou%27s_distorted_key_theory_for_peptide_drugs.

Introduction of Wenxiang Diagram
Using graphic approaches to study biological and medical systems can provide an intuitive vision and useful insights for helping analyze complicated relations therein, as indicated by many previous studies on a series of important biological topics, (see, e.g., [303]). Its importance can also be seen in an insightful Wikipedia article at https://en.wikipedia.org/wiki/Graph_theory_ in_enzymatic_kinetics. The wenxiang diagram [304] is a special kind of graphical approach, which is very useful for in-depth studying protein-protein interaction mechanism [305,306]. For more about the wenxiang diagram, see an insightful Wikipedia article at https://en.wikipedia.org/wiki/Wenxiang_diagram.

Predictors for Multi-Label Systems
Information of subcellular localization for a protein is indispensable for revealing its biological function. Therefore, one of the fundamental goals in molecular cell biology and proteomics is to determine the subcellular locations of proteins in an entire cell. Before 2007, most efforts in this regard were focused on the single-label system by assuming that each of the constitute proteins in a cell had one, and only one, subcellular location (see, e.g., [307][308][309][310][311]). However, with more experimental data uncovered, it has been found that many proteins may simultaneously occur or move between two or more location sites in a cell and hence need multiple labels to mark them. Proteins with multiple locations are also called multiplex proteins [312,313], which are often the special targets for drug development [313-319]). Therefore, how to deal with this kind of multi-label systems is a critical challenge. To take the challenge, the Institute has developed the following four series of predictors: (1) PLoc [313,320-326]; (2) iLoc [327-332]; (

Five-Steps Rule
The Institute was the birthplace of the famous 5-steps rule [272], which has been used in nearly all the areas of computational biology [203][204]215,[224][225][226][227][228][229][230]233,251,[254][255][256][259][260][261][264][265]277,279,288,), material science [369], and even the commercial science (e.g., the bank account systems). The only difference between the them is how to formulate the statistical samples or events with an effective mathematical expression that can truly reflect their intrinsic correlation with the target to be predicted. Like the case of many machine-learning algorithms, the "5-steps rule" can be widely used in nearly all the areas of statistical analysis. For more about the 5-steps rule, see an insightful Wikipedia article at https://en.wikipedia.org/wiki/5-step_rules. Working in such Institute filled with this kind of philosophy and atmosphere, the scientists would be more prone to be stimulated by the eight pioneering papers from the then Chairman of Nobel Prize Committee Sture Forsen [370][371][372][373][374][375][376][377] and many of their follow-up papers [172,189,305,348,, so as to drive them substantially more creative and productive.

Conclusion and Perspective
In comparison with the conventional institutes, Gordon Life Science Institute has the following unique advantages: it can (1) Attract those scientists who are really loving science more than anything else; (2) Maximize their creativity in science and minimize the distraction or disturbance caused by the relocation and various followed-up tedious things; (3) Provide them with an ideal environment to completely focus on doing science; (4) Drive their motivation by insightful imagination and intriguing curiosity; and (5) Create the atmosphere to guide their scientific results more truthful and wonderful.