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Biomedical subjects

William Bains

Publications and source records attributed to William Bains.

9 recordsLinked to original sources
PubMed2005

How to write up a hypothesis: the good, the bad and the ugly.

Medical Hypotheses exists to give ideas and speculations in medicine a fair hearing. Doing this is not easy. Most conventional journals would regard some of what is published here as questionable, most referees would reject it as 'unproven'. We have more liberal standards, for reasons we have presented before. But we still require 'good' science -- logical argument that is supported by fact and comes to interesting, even useful, conclusions. Alas, not everything received comes close to even this liberal standard. Since I joined the Editorial Board I have read about 130 submissions to Medical Hypotheses. They range from exciting and insightful papers that might be substantial advances in their field, to complete rubbish. I want to lay out what I believe to be the essence of the former so as to avoid having to read so much of the latter.

Models, Theoretical↗
PubMed2004

HERG binding specificity and binding site structure: evidence from a fragment-based evolutionary computing SAR study.

We describe the application of genetic programming, an evolutionary computing method, to predicting whether small molecules will block the HERG cardiac potassium channel. Models based on a molecular fragment-based descriptor set achieve an accuracy of 85-90% in predicting whether the IC(50) of a 'blind' set of compounds is <1 microM. Analysis of the models provides a 'meta-SAR', which predicts a pharmacophore of two hydrophobic features, one preferably aromatic and one preferably nitrogen-containing, with a protonatable nitrogen asymmetrically situated between them. Our experience of the approach suggests that it is robust, and requires limited scientist input to generate valuable predictive results and structural understanding of the target.

Animals↗
PubMed2004

Many chemistries could be used to build living systems.

It has been widely suggested that life based around carbon, hydrogen, oxygen, and nitrogen is the only plausible biochemistry, and specifically that terrestrial biochemistry of nucleic acids, proteins, and sugars is likely to be "universal." This is not an inevitable conclusion from our knowledge of chemistry. I argue that it is the nature of the liquid in which life evolves that defines the most appropriate chemistry. Fluids other than water could be abundant on a cosmic scale and could therefore be an environment in which non-terrestrial biochemistry could evolve. The chemical nature of these liquids could lead to quite different biochemistries, a hypothesis discussed in the context of the proposed "ammonochemistry" of the internal oceans of the Galilean satellites and a more speculative "silicon biochemistry" in liquid nitrogen. These different chemistries satisfy the thermodynamic drive for life through different mechanisms, and so will have different chemical signatures than terrestrial biochemistry.

Biochemical Phenomena↗
PubMed2004

Paradoxes of non-trivial gene networks: how cancer-causing mutations can appear to be cancer-protective.

Abnormalities of gene structure or expression are commonly found in cancers, where they are used as prognostic markers, predicting the likely severity of disease or chances of response to therapy. An odds ratio (OR) of <1 indicates that a marker's presence is correlated with better outcome. An OR of <1 is also often taken to mean that the gene concerned has a protective effect in the mechanism of cancer. I show that this is not necessarily so. Modeling of the genes involved in the causation of cancer as a network of weak, failure-prone elements shows that "cancer-causing" genes (i.e., genes whose abnormality is causal in driving cancer) can nevertheless appear as "protective" markers in later stage cancers. This implies that results suggesting that well-known oncogenes have an OR of <1 are quite valid, and that predicting a "protective" role from an apparently protective prognostic value is not valid. I identify mdm-2 and bax as candidates for genes with an apparently protective role through this mechanism.

Gene Expression Regulation↗
PubMed2003

Vasoprotective VEGF as a candidate for prevention of recurrence of fibrotic diseases such as Dupuytren's contracture.

Dupuytren's contracture is a disease caused by the proliferation of contractile, fibroblastic cells adjacent to the palmar fascia of the hand. Cellular proliferation is apparently related to similar 'fibroblast' proliferation in wound healing, but continues in the absence of wounding. I propose that this is a similar processes to that which happens in the vascular wall during vascular surgery, that the myofibroblasts are at least partially similar to smooth muscle cells in phenotype, and consequently that treatment with VEGF, either as protein or via gene therapy, which has proven successful in controlling aberrant, wounding-related cell proliferation in arterial grafting, may be valuable in preventing recurrence of Dupuytren's disease after surgery.

Dupuytren Contracture↗
PubMed2003

Silicon chemistry as a novel source of chemical diversity in drug design.

The use of organosilicon chemistry in drug design is reviewed. The field of bioorganosilicon chemistry, which sprung up in the 1970s to exploit the opportunities of silicon for drug design, is currently being developed into a practical and commercial enterprise. This review is mainly focused on two different approaches: (i) synthesizing a silicon analog of a known drug in which one carbon atom has been replaced by a silicon atom, with the rest of the molecule being identical (carbon/silicon switch, sila-substitution); (ii) synthesizing completely new silicon-based classes of compounds (the carbon analogs of which do not exist) that exploit specific features of silicon chemistry to address a well-validated target.

Amino Acids↗
PubMed2002

Evolutionary computational methods to predict oral bioavailability QSPRs.

This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico.

Animals↗