William M. Southerland

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BACKGROUND Transcription of HIV-1 genes is activated by HIV-1 Tat protein, which induces phosphorylation of RNA polymerase II (RNAPII) C-terminal domain (CTD) by CDK9/cyclin T1. Earlier we showed that CDK2/cyclin E phosphorylates HIV-1 Tat in vitro. We also showed that CDK2 induces HIV-1 transcription in vitro and that inhibition of CDK2 expression by RNA(More)
Residue interaction networks and loop motions are important for catalysis in dihydrofolate reductase (DHFR). Here, we investigate the effects of ligand binding and chain connectivity on network communication in DHFR. We carry out systematic network analysis and molecular dynamics simulations of the native DHFR and 19 of its circularly permuted variants by(More)
In recent years, virtual database screening using high-throughput docking (HTD) has emerged as a very important tool and a well-established method for finding new lead compounds in the drug discovery process. With the advent of powerful personal computers (PCs), it is now plausible to perform HTD investigations on these inexpensive PCs. To make HTD more(More)
A contact map is a key factor representing a specific protein structure. To simplify the protein contact map prediction, we predict the inter-residue contact clusters centered at the groups of their surrounding inter-residue contacts. In this paper, we adopt a Support Vector Machine (SVM)-based approach to predict the inter-residue contact cluster centers.(More)
High-Throughput Docking has emerged as a well establish method for identifying lead components in the process of searching for new drugs. The High-Throughput Docking Service provides researchers with the ability to do drug screening using tools usually reserved for large research centers. The service provides web-based access to large clusters of computers(More)
Alcohol abuse and alcoholism are serious and costly problem in USA. Thus, the development of anti-alcoholism agents could be very significant. The understanding of the neurochemical basis underlying the addictive properties of drugs of abuse is imperative for the development of new pharmacological means to reverse the addictive state, prevent relapse or to(More)
Protein fold classification is a key step to predicting protein tertiary structures. This paper proposes a novel approach based on genetic algorithms and feature selection to classifying protein folds. Our dataset is divided into a training dataset and a test dataset. Each individual for the genetic algorithms represents a selection function of the feature(More)