The last decade has contributed to our understanding of the three-dimensional structure of the human immunodeficiency virus, type 1 (HIV-1) integrase (IN) and to the description of how the enzyme catalyzes the viral DNA integration into the host DNA. Recognition of the viral DNA termini by IN is sequence-specific, and that of the host DNA does not require particular sequence, although in physicochemical studies IN fails to discriminate between the two interactions. Here, such discrimination was allowed thanks to a model system using designed oligonucleotides and peptides as binding structures. Spectroscopic (circular dichroism, NMR, and fluorescence anisotropy) techniques and biochemical (enzymatic and filter binding) assays clearly indicated that the amphipathic helix ␣4, located at the catalytic domain surface, is responsible for the specific high affinity binding of the enzyme to viral DNA. Analogues of the ␣4 peptide having increased helicity and still bearing the biologically relevant lysines 156 and 159 on the DNA binding face, and oligonucleotides conserving an intact attachment site, are required to achieve high affinity complexes (K d of 1.5 nM). Data corroborate previous in vivo results obtained with mutated viruses.

Computational chemistry is a scientific field within which the computer is a pivotal element. This scientific community emerged in the eighties and was involved with two major industries: the computer manufacturers and the pharmaceutical industry, the latter becoming a potential market for the former through molecular modeling software packages. We aim to address the difficult relationships between scientific modeling methods and the software implementing these methods throughout the nineties. Developing, using, licensing and distributing software leads to multiple tensions among the actors in intertwined academic and industrial contexts. The Computational Chemistry mailing List (CCL), created in 1991, constitutes a valuable corpus for revealing the tensions associated with software within the community. We analyze in detail two flame wars which exemplify these tensions. We conclude that models and software must be addressed together. Interrelations between both imply that openness in computational science is complex.1 Keywords scientific software, computational chemistry, software users, openness, history of chemistry, mailing list, flame warsThe quotation in the title, taken from a scientific mailing list, the "Computational Chemistry List", is intended to illustrate the tensions around the use of software in a scientific community. "Computational chemists", gathered around the uses of computers in chemistry [1], belong to a scientific field which started to grow in the eighties, whose aim was to develop "computational tools and techniques [which] offer a new method of attack in the continuing effort [in the chemical community] to obtain chemical information" [2]. Thus, the computer is a pivotal element of this scientific community, even though it is considered here as a tool, not as the object of the science in question. The adjective "computational", a typical word from the eighties and nineties, is essential: it is a scientific world of "computational science", not "computer science".Numerous studies deal with the relations between computing and scientific activity, some of which are even considered as classics. Themes such as the "computerization of science" [3] or, for example, the mutual shaping of computing and biology [4] or the emergence of computerized evidence-based medicine [5] explore their interplay. Computational science has been addressed by scholars, for example the philosophical significance of its rise for scientific method [6], or the emergence of Monte Carlo simulations [7]. Many works also exist in the history of software [8], either on the software viewed as an industrial [9] or professional [10] activity, or on the difficulty and complexity of writing such a history [11]. Yet, software per se in computational science has attracted less attention, even if Spencer has conducted an ethnographic research within a computational fluid dynamics laboratory on a piece of software [12].Our way to address the issue of software in computational science is to focus on application software in computat...

Computational reproducibility (i.e. issues of reproducibility stemming from the computer as a scientific tool) possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics (transparency, consistency, sustainability and inclusivity) as key to the role of software in computational reproducibility.

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