Department of Biochemistry and Structural Biology, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, México DF, México.
PLoS One. 2011;6(6):e21399. doi: 10.1371/journal.pone.0021399. Epub 2011 Jun 28.
Exhaustive prediction of physicochemical properties of peptide sequences is used in different areas of biological research. One example is the identification of selective cationic antibacterial peptides (SCAPs), which may be used in the treatment of different diseases. Due to the discrete nature of peptide sequences, the physicochemical properties calculation is considered a high-performance computing problem. A competitive solution for this class of problems is to embed algorithms into dedicated hardware. In the present work we present the adaptation, design and implementation of an algorithm for SCAPs prediction into a Field Programmable Gate Array (FPGA) platform. Four physicochemical properties codes useful in the identification of peptide sequences with potential selective antibacterial activity were implemented into an FPGA board. The speed-up gained in a single-copy implementation was up to 108 times compared with a single Intel processor cycle for cycle. The inherent scalability of our design allows for replication of this code into multiple FPGA cards and consequently improvements in speed are possible. Our results show the first embedded SCAPs prediction solution described and constitutes the grounds to efficiently perform the exhaustive analysis of the sequence-physicochemical properties relationship of peptides.
对肽序列理化性质的详尽预测被应用于不同的生物研究领域。例如，选择性阳离子抗菌肽（SCAP）的鉴定，它可用于治疗不同的疾病。由于肽序列具有离散性，理化性质的计算被认为是一个高性能计算问题。针对此类问题的一种有竞争力的解决方案是将算法嵌入专用硬件中。在本工作中，我们将用于 SCAP 预测的算法改编、设计和实现到现场可编程门阵列（FPGA）平台中。将四个有用的理化性质代码实现到 FPGA 板中，这些代码可用于鉴定具有潜在选择性抗菌活性的肽序列。与单个 Intel 处理器的单个周期相比，在单副本实现中获得的加速高达 108 倍。我们设计的固有可扩展性允许将此代码复制到多个 FPGA 卡中，从而可以提高速度。我们的结果展示了第一个嵌入式 SCAP 预测解决方案，并为有效地执行肽序列理化性质关系的详尽分析奠定了基础。
