Virtual Screening and Drug Docking, Volume 59 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Can docking scoring functions guarantee success in virtual screening , No dance, no partner! A tale of flexibility in docking and virtual screening, Handling Imbalance Data in Virtual Screening, Rational computational approaches to predict novel drug candidates against leishmaniasis, Virtual screening against Mtb DNA gyrase: Applications and success stories, Using Filters in Virtual Screening: A Brief Guide to Minimize Errors and Maximize Efficiency, and more.
Additional chapters in the new release include Machine Learning and Deep Learning Strategies for Virtual Screening, Applications of the Virtual Screening to find the novel HIV-1 therapeutic agents, and Large-scale screening of small molecules with docking strategies and its impact on drug discovery.
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Annual Reports on Medicinal Chemistry series
- Updated release includes the latest information on Virtual Screening and Drug Docking
1. Can docking scoring functions guarantee success in virtual
screening?
Yunierkis Perez-Castillo
2. No dance, no partner! A tale of flexibility in docking and virtual
screening
Attilio Vittorio Vargiu
3. Handling Imbalance Data in Virtual Screening
Selçuk Korkmaz
4. Rational computational approaches to predict novel drug candidates against
leishmaniasis
Rodrigo Ochoa, Christian Bustamante and Carlos Muskus
5. Virtual screening against Mtb DNA gyrase: Applications and success
stories
Dharmarajan Sriram
6. Using Filters in Virtual Screening: A Brief Guide to Minimize Errors and
Maximize Efficiency
Mohammad A. Ghattas V
7. Machine Learning and Deep Learning Strategies for Virtual Screening
Waqar Hussain
8. Applications of the Virtual Screening to find the novel HIV-1 therapeutic
agents
Sanjeev Kumar Singh
9. Large-scale screening of small molecules with docking strategies and its
impact on drug discovery
Sanjeev Kumar Singh
Julio Caballero studied Chemistry at Universidad de La Habana, where he graduated with a Gold Diploma in 2001. In 2002-2004 he worked on protein engineering in the Enzyme Technology Group at Universidad de Matanzas. He began to work on pharmaceutical modeling and artificial intelligence in 2004 and founded the Molecular Modeling Group at the same university. In 2006 he moved to Talca, Chile and began to work at Universidad de Talca. He was incorporated into the Ph.D. program in Applied Sciences in 2008. He completed his Ph.D. degree working in computational biochemistry in 2012 and was appointed as Assistant Professor at Universidad de Talca. Recently, he was promoted to Full Professor at the same university. At this moment Julio Caballero is member of the regular academic staff of Universidad de Talca, head of the department of Bioinformatics, researcher at the Centro de Bioinformática, Simulación y Modelado (CBSM), and lecturer of the School of Civil Engineering in Bioinformatics at the Faculty of Engineering at the same university
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