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Abstract

Virtual screening (VS) of chemical libraries formatted in silico provides an alternative to experimental high-throughput screening (HTS) for the identification of small molecule modulators of protein function. We have tailored a VS approach combining fingerprint similarity searching and support vector machine modeling toward the identification of small molecular probes for the study of cytohesins, a family of cytoplasmic regulator proteins with multiple cellular functions. A total of 40 new structurally diverse inhibitors were identified, and 26 of these compounds were more active than the primary VS template, a single known inhibitory chemotype, in at least one of three different assays (guanine nucleotide exchange, Drosophila insulin signaling, and human leukocyte cell adhesion). Moreover, these inhibitors displayed differential inhibitory profiles. Our findings demonstrate that, at least for the cytohesins, computational extrapolation from known active compounds was capable of identifying small molecular probes with highly diversified functional profiles.