Santosh Panjikar, Victor Lamzin, Paul A Tucker, Manfred S Weiss
{"title":"A short history of Auto-Rickshaw.","authors":"Santosh Panjikar, Victor Lamzin, Paul A Tucker, Manfred S Weiss","doi":"10.1107/S2059798326008831","DOIUrl":null,"url":null,"abstract":"<p><p>Auto-Rickshaw was developed in the early 2000s at EMBL Hamburg as an automated macromolecular structure-determination platform for crystallography and structural biology. Its initial motivation was to provide beamline users with rapid feedback on whether diffraction data were sufficient for structure solution. The platform was not merely a wrapper around existing crystallographic programs; it encoded the expert decisions needed to select phasing, density-modification, model-building and refinement protocols according to the information available from the experiment. Since its first publication in 2005, Auto-Rickshaw has supported a broad range of experimental and model-based strategies, including SAD, MAD, SIR, SIRAS, RIP, molecular replacement and hybrid approaches such as MRSAD. A central feature was the integration of the SHELX programs, particularly SHELXC, SHELXD and SHELXE, whose speed, robustness and command-line design made them especially suitable for automated pipelines. This review gives a brief historical account of Auto-Rickshaw, the beamline context in which it emerged, the design principles that shaped it and the role of SHELX programs in its phasing architecture. It also considers the broader legacy of Auto-Rickshaw as a bridge between crystallographic expertise and automated, reproducible structure solution. Finally, the review places Auto-Rickshaw in the current landscape of synchrotron technologies, high-throughput structural biology, containerized deployment, predicted structural models and AI-assisted decision making, where reliable automation remains essential.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"1139-1151"},"PeriodicalIF":4.3000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13632750/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Crystallographica. Section D, Structural Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1107/S2059798326008831","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/9/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Auto-Rickshaw was developed in the early 2000s at EMBL Hamburg as an automated macromolecular structure-determination platform for crystallography and structural biology. Its initial motivation was to provide beamline users with rapid feedback on whether diffraction data were sufficient for structure solution. The platform was not merely a wrapper around existing crystallographic programs; it encoded the expert decisions needed to select phasing, density-modification, model-building and refinement protocols according to the information available from the experiment. Since its first publication in 2005, Auto-Rickshaw has supported a broad range of experimental and model-based strategies, including SAD, MAD, SIR, SIRAS, RIP, molecular replacement and hybrid approaches such as MRSAD. A central feature was the integration of the SHELX programs, particularly SHELXC, SHELXD and SHELXE, whose speed, robustness and command-line design made them especially suitable for automated pipelines. This review gives a brief historical account of Auto-Rickshaw, the beamline context in which it emerged, the design principles that shaped it and the role of SHELX programs in its phasing architecture. It also considers the broader legacy of Auto-Rickshaw as a bridge between crystallographic expertise and automated, reproducible structure solution. Finally, the review places Auto-Rickshaw in the current landscape of synchrotron technologies, high-throughput structural biology, containerized deployment, predicted structural models and AI-assisted decision making, where reliable automation remains essential.
期刊介绍:
Acta Crystallographica Section D welcomes the submission of articles covering any aspect of structural biology, with a particular emphasis on the structures of biological macromolecules or the methods used to determine them.
Reports on new structures of biological importance may address the smallest macromolecules to the largest complex molecular machines. These structures may have been determined using any structural biology technique including crystallography, NMR, cryoEM and/or other techniques. The key criterion is that such articles must present significant new insights into biological, chemical or medical sciences. The inclusion of complementary data that support the conclusions drawn from the structural studies (such as binding studies, mass spectrometry, enzyme assays, or analysis of mutants or other modified forms of biological macromolecule) is encouraged.
Methods articles may include new approaches to any aspect of biological structure determination or structure analysis but will only be accepted where they focus on new methods that are demonstrated to be of general applicability and importance to structural biology. Articles describing particularly difficult problems in structural biology are also welcomed, if the analysis would provide useful insights to others facing similar problems.