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Editorial Editorial: The Concepts of Pharmacophore/Toxicophores: A Philosophical/Mathematical-cum-Historical Perspective 1. INTRODUCTION Nothing exists except atoms and empty space; everything else is opinion. Democritus The soul never thinks without a picture. Aristotle The safest general characterization of the European philosophical tradition is that it consists of a series of footnotes to Plato. Alfred North Whitehead “To say that Forms are patterns and that other things participate in them is emptytalk, mere poetic metaphors.” Aristotle – Metaphysics During the last half century, the concept of pharmacophore has gradually assumed an important position in computer-assisted drug discovery [1-6]. These days the concept of pharmacophore is ubiquitous in the pharmacological literature and drug discovery research. Some commercial software is also Available to facilitate the generation of pharmacophores [7]. Historically, it is recognized that an initial idea of pharmacophore was first proposed by Paul Ehrlich in 1909 as "a molecular framework that carries (phoros) the essential features responsible for a drug’s (=pharmacon's) biological activity [8]. 2. THE PHILOSOPHICAL BASIS Here we felt it is appropriate to discuss the origin of pharmacophore from a philosophical/ epistemological point of view. The perennial problem in the philosophy of science and scientific research is to strike the balance between general ideas (universals) and specific phenomena (particulars). Plato and Aristotle exemplify the two mutually opposite classes of thinkers/ scientist: those who seek similarities, and general patterns (universals) vis-à-vis those who emphasize the differences, varieties and specifics (particulars) in the phenomenal world [9]. The modeling process in predictive pharmacology and toxicology consists of selecting certain aspects of molecular structure while ignoring others. As noted by Albert Einstein [10] in his remarks on the philosopher Bertrand Russell’s theory of knowledge: “The more, however, we turn to the most primitive concepts of everyday life, the more difficult it becomes amidst the mass of inveterate habits to recognize the concept as an independent creation of thinking. It was thus that the fateful conception – fateful, that is to say, for an understanding of the here-existing conditions – could arise, according to which the concepts originate from experience by way of "abstraction," i.e., through omission of a part of its content.” 3. ABSTRACTION OF PHARMACOPHORE FROM SPECIFIC SET OF CHEMICALS The guiding motto in the life of every natural philosopher should be, seek simplicity and distrust it. Alfred North Whitehead "Computers are incredibly fast, accurate, and stupid. Human beings are incredibly slow, inaccurate, and brilliant. Together they are powerful beyond imagination." Albert Einstein A pharmacophore is usually a recognized 3-D substructural pattern contained in a chemical structure that is responsible for its medicinal activity [1-6]. Groups of molecules possessing similar pharmacological profiles and a narrow range of physicochemical characteristics are put into a “pharmacophoric class” in terms of structural factors and /or biomedically important physicochemical properties s like hydrophobicity, aromaticity, hydrogen bond (HB) donor acidity, cations, HB acceptor basicity, etc. In the realm of toxicology, structural features known as “toxicophores” or “structural alerts” are used to identify chemical structures possessing a specific type of toxicity or adverse drug reaction (ADR) based either on substructures or reactive groups that are related to toxicity, carcinogenicity, mutagenicity, etc. [11, 12]. Because substructures, being of graph-theoretic in origin, are essentially two-dimensional entities, toxicophores may also be two dimensional in addition to three dimensional, as indicated in Fig. (1). We give below a couple of examples of pharmacophores: 3.1. Muscarinic Pharmacophore Muscarinic acetylcholine receptors (mAChRs) are acetylcholine receptors which form G protein-receptor complexes in the cell membranes of certain neurons and other cells. They act as the main end-receptor stimulated by acetylcholine released from postganglionic fibers in the parasympathetic nervous system. In 1967, Kier [1] formulated the concept muscarinic receptor based on molecular orbital calculation of preferred conformations of acetylcholine, muscarine, and muscarone. 1573-4099/18 $58.00+.00
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Collect2Dor3Dstructuresofaset ofmoleculesalongwiththeir pharmacologicalortoxicitydata
Observe/enumerate2Dor3=D featuresinthemolecules
Extractessentialpharmacophoricor toxicophoricfeaturesbytheinductive method Fig. (1). Schematic representation of the process for the discovery of pharmacophoric or toxicophoric patterns.
3.2. Pharmacophore for Mosquito Repellency Discovery of safer and more effective repellents is necessary for the protection from mosquito bites. Repellents do not all share a single mode of action. Therefore, pharmacophoric modeling approach has been used to discover novel repellents. In pursuit of discovery of new repellents, Bhattacharjee et al. [13] developed a pharmacophore that consisting of three hydrophobic sites and a hydrogen-bond acceptor site in specific locations around the three- dimensional space of the known repellents. It is noteworthy that pharmacophores described in items 3.1 and 3.2 above are not independently existing entities, but they are embedded in particular molecules along with other structural features. They can be used to screen chemical databases for potential drugs. But one needs to be aware that if a compound is flagged based on a pharmacophoric pattern, that does not mean that the compound will have desirable biological properties. We face the important problems of false positives [14]. Therefore, experimental validation of the results of pharmacophore based screening of databases is essential [15]. 4. MATHEMATICAL BASIS: BINARY RELATION AND PHARAMCOPHORE/TOXICOPHORE EXTRACTION In the formulation of pharmacophore/ toxicophore, the chemicals are characterized in terms of a set of properties shared by them [1-3] or using an abstraction process [10]. From the viewpoint of mathematics and binary relations defined on sets, an equivalence relation [16] or a tolerance relation [17] on the set of candidate chemicals can be used to extract pharmacophoric subsets. It is known from data on chemical carcinogenesis (18) the 5-nitrofuran type antibacterial agents are potent carcinogens. If we define the 5-nitrofuran moiety as the toxicophore for carcinogenesis, a binary relation R on a three chemicals A, B, and C belonging to the set S of chemicals having 5-nitroufran substructure will have the following properties: 1.
A R A (reflexive property; for all elements A S
2.
For all elements in the set S, if A R B, then B R A (symmetric property)
3.
For all elements A, B. C S, if A R B and B R C, then A R C (transitive property)
It is well known that an equivalence relation decomposes a set into disjoint subsets [16]. Application of the above relation on a large library of chemicals like Maybridge [19] will extract all 5-nitrofuran derivatives into a subset and others not containing the substructure into another subset. In the case of the pharmacophore for repellency, consisting of three hydrophobic sites and a hydrogen-bond acceptor site distributed in the three dimensional space the situation is more complicated as compared to the 5-nitrofuran toxicophore case. In the latter case, the pharmacophoric determinant was a binary (0/1) variable, but for the repellency the four attributes and their mutual distances will be real numbers on a continuous scale. Various types of matrices have been defined for the characterization of molecular graphs that arise in chemistry [20]. The three-dimensional analogs of such matrices can be useful in the characterization and comparison of 3-D pharmacophore for the repellency and others. 5. THE CASE OF NON-SPECIFIC TOXICITY In the case of non-specific drugs like anesthetics or narcotic industrial chemicals in the Toxic Substances Control Act (TSCA) Inventory, they do not usually possess definite pharmacophoric patterns. Their biochemical action is determined by general thermodynamic properties like chemical potential [21, 22] or general properties like octanol-water partition coefficient [23]. 6. QUO VADIMUS? As indicated above, the extraction of pharmacophore or toxicophore from a set of chemicals is a tendency toward the “universal” from a set of particulars, i.e., a collection of specific chemical structures and their biolog8ical test data. Depending on the situation either of the two well- known binary relations, viz., equivalence relation or tolerance relation, may be used for this purpose.
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But we must keep in mind that such pharmacophores/ toxicophores, being abstract features, must exist as specific instances in individual molecules where they are embedded in or mixed with other structural features which may modify their pharmacophoric potential. That is why it has been suggested that when a set of candidate pharmacophoric chemicals are selected from the screening of databases using computerderived pharmacophores, they must be validated experimentally using laboratory test data [15]. For so called non-specific chemicals, general properties like octanol-water partition coefficient or chemical potential can predict their biological action without the use of any specific pharmacophore. More recently, Kier and Hall [24] proposed that “proton hopping” is the “ultimate trigger” that elicits the measurable biological response during the interaction of the molecules with the biological targets/ receptors. Further research is needed to connect the proton hopping process with the mode/ mechanism of biologically active molecules, both specific and non-specific. CONFLICT OF INTEREST The authors declare that there is no conflict of interest. ACKNOWLEDGEMENT One of the authors (SCB) is grateful to Dr. Apurba K. Bhattacharjee for extensive discussion and collaboration in the use of pharmacophore in computer-aided drug design. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10]
[11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24]
Kier, L. B. Molecular orbital calculation of preferred conformations of acetylcholine, muscarine, and muscarone. Mol. Pharmacol. 1967, 3, 487-494. Kier, L. B. Molecular orbital theory in drug research, academic press, New York, 1971. Kier, L. B. In fundamental concepts in drug–receptor interactions, J. F. Danielli, J. F. Moran and D. J. Triggle, Eds., 1970. Academic Press, New York, 1970 (Proceedings of a 1968 symposium). Güner, O. F. Manual pharmacophore generation: Visual pattern recognition, in Pharmacophore, perception, development, and use in drug design, O.F. Güner, eds., University International Line (IUL Biotechnology Series), San Diego, 2000, pp.17-20. Bhattacharjee, A. K.; Marek, E.; Le, H. T.; and Gordon, R. K. Discovery of non-oxime reactivators using an in silico pharmacophore model of oxime reactivators of OP-inhibited acetylcholinesterase. Eur. J. Med. Chem., 2012, 49, 229-238. Van Drie, J. H. 2007. Monty kier and the origin of the pharmacophore concept. Internet Electronic Journal of Molecular Design, 2007, 6, 271-279. Discovery Studio, DS Version 2.5, Accelrys Inc., San Diego, CA, 2007, http://accelrys.com/products/discovery-studio/ Paul Ehrlich, P. Partial Cell Functions: Nobel Lecture, December 11, 1908: (Ref: ttps://www.nobelprize.org/nobel_prizes/medicine/laureates/1908/ ehrlich-lecture.html; Accessed on 20 May, 2017). Ball, P. Decoding deep similarities. Nature, 2017, 545, 154. Einstein, A. Remarks on Bertrand Russell’s Theory of Knowledge, In: Ideas and Opinions by Albert Einstein, pp. 18-24, Ed. Carl Seelig, (Based on MEIN WELTBILD, edited by Carl Seelig, and other sources; New translations and revisions by Sonja Bargmann), Crown Publishers, Inc., 1954, New York. Plonik, A.: Marjan Vrako, M.; Dolenc, M. S. Mutagenic and carcinogenic structural alerts and their mechanisms of action. Arh. Hig. Rada. Toksikol., 2016, 67, 169-182. Sushko, I.; Salmina, E.; Potemkin, V. A.; Poda, G.; Tetko, I. V. ToxAlerts: A web server of structural alerts for toxic chemicals and compounds with potential adverse reactions. J. Chem. Inf. Model., 2012, 52, 2310-2316. Bhattacharjee, A. K.; Dheranetra, W.; Nichols, D. A.; Gupta, R. K. 3D pharmacophore model for insect repellent activity and discovery of new repellent candidates. QSAR Comb. Sci., 2005, 24, 593-602. E. K. Davies and C. J. Davies, towards understanding false positives in Structure-Based Virtual Screening; http://www.treweren.com/ falsepositives.html Basak, S. C.; Bhattacharjee, A. K. Importance of experimental validation of pharmacophore based virtual screening of compound databases. Curr. Comput. Aided Drug Des., 2015, 11, 1-2. Green, J. A. Sets and Groups, The english language book society & rutledge and kegan paul: Surrey, England, 1965. Basak, S.C.; Grunwald, G.D. Tolerance space and molecular similarity. SAR QSAR Environ. Res., 1995, 3, 265-277. Arcos, J.C. Structure-activity relationships: Criteria for predicting the carcinogenic activity of chemical compounds. Environ. Sci. Technol., 1987, 21, 743-745 Maybridge screening collections and fragment libraries for drug discovery. Available from: http://www.maybridge.com/. (Accessed 11 June, 2017). Janezic, D.; Milicevic, A.; Nikolic, S.; Trinajstic, N. Graph-Theoretical Matrices in Chemistry, CRC Press, Roca Raton, Fl, 2017. Ferguson, J. The use of chemical potential as indices of toxicity, Proc. R. Soc., London Ser. B., 1939, 127, 387-404. Mullins, L. J. Some physical mechanisms in NON, Chem. Rev., 1954, 54, 289-323. Veith, G. D., Call, D. J., Brooke, L. T. Structure-toxicity relationships for the fathead minnow, Pimephales promelas: Narcotic industrial chemicals. Can. J. Fish. Aquat. Sci., 1983, 40, 743-748. Kier, L.B.: Hall, L.H. The creation of proton hopping from a drug-receptor encounter. Chem. Biodivers., 2013, 16, 2221-2225.
Dr. Lemont B. Kier (Co-Editor) Virginia Common Wealth University Richmond, VA USA E-mail:
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Dr. Subhash C. Basak (Editor-in-Chief) Natural Resources Research Institute Department of Chemistry & Biochemistry University of Minnesota Duluth Duluth, MN 55811 USA E-mail:
[email protected] 