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Biomedical subjects

C D Rosin

Publications and source records attributed to C D Rosin.

4 recordsLinked to original sources

Coevolution and subsite decomposition for the design of resistance-evading HIV-1 protease inhibitors.

Drug resistance sharply limits the effectiveness of human immunodeficiency virus (HIV) protease inhibitors in acquired immunodeficiency syndrome therapy. In previous work, we presented methods for design of resistance-evading inhibitors using a computational coevolution technique. Here, we report subsite decomposition experiments that examine the relative importance and roles of each subsite in HIV protease, and the constraints on robust inhibitor design that are imposed by possible resistance mutations in each subsite. The results identify several structural features of robust resistance-evading inhibitors for use in drug design, and show their basis in the constraints imposed by the range of allowable mutation in the protease. In particular, the results identify the P3 and P3' sites as being particularly sensitive to protease mutation: inhibitors designed to fill the S3 and S3' sites of the wild-type protease will be susceptible to viral resistance, but inhibitors with side-chains smaller than a phenylalanine residue at P3 and P3', preferably medium-sized amino acids in the range from valine to leucine and isoleucine residues, will be more robust in the face of protease resistance mutation.

Computational Biology↗

Coevolutionary analysis of resistance-evading peptidomimetic inhibitors of HIV-1 protease.

We have developed a coevolutionary method for the computational design of HIV-1 protease inhibitors selected for their ability to retain efficacy in the face of protease mutation. For HIV-1 protease, typical drug design techniques are shown to be ineffective for the design of resistance-evading inhibitors: An inhibitor that is a direct analogue of one of the natural substrates will be susceptible to resistance mutation, as will inhibitors designed to fill the active site of the wild-type or a mutant enzyme. Two design principles are demonstrated: (i) For enzymes with broad substrate specificity, such as HIV-1 protease, resistance-evading inhibitors are best designed against the immutable properties of the active site-the properties that must be conserved in any mutant protease to retain the ability to bind and cleave all of the native substrates. (ii) Robust resistance-evading inhibitors can be designed by optimizing activity simultaneously against a large set of mutant enzymes, incorporating as much of the mutational space as possible.

Amino Acid Sequence↗

Computational coevolution of antiviral drug resistance.

An understanding of antiviral drug resistance is important in the design of effective drugs. Comprehensive features of the interaction between drug designs and resistance mutations are difficult to study experimentally because of the very large numbers of drugs and mutants involved. We describe a computational framework for studying antiviral drug resistance. Data on HIV-1 protease are used to derive an approximate model that predicts interaction of a wide range of mutant forms of the protease with a broad class of protease inhibitors. An algorithm based on competitive coevolution is used to find highly resistant mutant forms of the protease, and effective inhibitors against such mutants, in the context of the model. We use this method to characterize general features of inhibitors that are effective in overcoming resistance, and to study related issues of selection pathways, cross-resistance, and combination therapies.

Algorithms↗

New methods for competitive coevolution.

We consider "competitive coevolution," in which fitness is based on direct competition among individuals selected from two independently evolving populations of "hosts" and "parasites." Competitive coevolution can lead to an "arms race," in which the two populations reciprocally drive one another to increasing levels of performance and complexity. We use the games of Nim and 3-D Tic-Tac-Toe as test problems to explore three new techniques in competitive coevolution. "Competitive fitness sharing" changes the way fitness is measured; "shared sampling" provides a method for selecting a strong, diverse set of parasites; and the "hall of fame" encourages arms races by saving good individuals from prior generations. We provide several different motivations for these methods and mathematical insights into their use. Experimental comparisons are done, and a detailed analysis of these experiments is presented in terms of testing issues, diversity, extinction, arms race progress measurements, and drift.

Algorithms↗