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Register a new userFPScreen: A Rapid Similarity Search Tool for Massive Molecular Library Based on Molecular Fingerprint Comparison
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Added by
Tianmou Liu
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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We designed a fast similarity search engine for large molecular libraries: FPScreen. We downloaded 100 million molecules structure files in PubChem with SDF extension, then applied a computational chemistry tool RDKit to convert each structure file into one line of text in MACCS format and stored them in a text file as our molecule library. The similarity search engine compares the similarity while traversing the 166-bit strings in the library file line by line. FPScreen can complete similarity search through 100 million entries in our molecule library within one hour. That is very fast as a biology computation tool. Additionally, we divided our library into several strides for parallel processing. FPScreen was developed in WEB mode.
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Molecular similarity search has been widely used in drug discovery to identify structurally similar compounds from large molecular databases rapidly. With the increasing size of chemical libraries, there is growing interest in the efficient acceleration of large-scale similarity search. Existing works mainly focus on CPU and GPU to accelerate the computation of the Tanimoto coefficient in measuring the pairwise similarity between different molecular fingerprints. In this paper, we propose and optimize an FPGA-based accelerator design on exhaustive and approximate search algorithms. On exhaustive search using BitBound & folding, we analyze the similarity cutoff and folding level relationship with search speedup and accuracy, and propose a scalable on-the-fly query engine on FPGAs to reduce the resource utilization and pipeline interval. We achieve a 450 million compounds-per-second processing throughput for a single query engine. On approximate search using hierarchical navigable small world (HNSW), a popular algorithm with high recall and query speed. We propose an FPGA-based graph traversal engine to utilize a high throughput register array based priority queue and fine-grained distance calculation engine to increase the processing capability. Experimental results show that the proposed FPGA-based HNSW implementation has a 103385 query per second (QPS) on the Chembl database with 0.92 recall and achieves a 35x speedup than the existing CPU implementation on average. To the best of our knowledge, our FPGA-based implementation is the first attempt to accelerate molecular similarity search algorithms on FPGA and has the highest performance among existing approaches.
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