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Articles by Sameer Velankar
Fragment screening in focus
Main text Manfred S. Weiss Helmholtz-Zentrum Berlin, Macromolecular Crystallography Uwe Mueller Helmholtz-Zentrum Berlin, Macromolecular Crystallography Crystallographic fragment screening (CFS) is a powerful and information-rich technique that uses structure determination by X-ray crystallography as readout to detect the binding of small organic molecules (fragments) to biological macromolecules, typically proteins.
PROTEINS: Structure, Function, and Bioinformatics
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PROTEINS: Structure, Function, and Bioinformatics
1 Introduction The critical assessment of structure prediction (CASP) drives progress in computational structural biology through large-scale community experiments. Participants submit calculated structures that are evaluated using a range of metrics, and the results are assessed by independent scientists. The Center for CASP at UC Davis serves as the operational engine of CASP, providing the infrastructure for the experiments and handling all submitted and calculated data (Figure 1).
Toward a new economics of science
W.J. Baumol et al. The Theory of Environmental Policy: Externalities, Public Outlays, and the Quality of Life (1975) J.D. Bernal The Social Function of Science (1939) D.M. Blank et al. The Demand and Supply of Scientific Personnel (1957) S. Blume Toward a Political Sociology of Science (1974) S. Blume The Theoretical Significance of Co-operative Research D.
Biomolecular Interaction Prediction in the Pre‐ and Post‐AlphaFold Era: The 8th CAPRI Evaluation
1 Introduction Biomolecular interactions govern a wide range of cellular and intercellular activities. Characterizing these interactions at the atomic level is essential for understanding the mechanisms underlying health and disease and for developing new therapeutics.
The need to implement FAIR principles in biomolecular simulations - Nature Methods
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In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm.
By Rommie Amaro, Ivet Bahar, Massimiliano Bonomi, Gregory Bowman, Giovanni Bussi, Christophe Chipot, G. Andrés Cisneros, Peter Coveney, Roberto Covino, Matteo Dal Peraro, Lucie Delemotte, Jonathan W. Essex, Franca Fraternali, Francesco L. Gervasio, Fernando González-Nilo, Helmut Grubmüller, Marina G. Guenza, Horacio V. Guzman, Teresa Head-Gordon, Niu Huang, Xuhui Huang, Gerhard Hummer, Wanting Jiao, Syma Khalid, Charles A. Laughton, Kresten Lindorff-Larsen, Sharon M. Loverde, Magnus Lundborg, Yun Luo, F. Javier Luque, Charlotte Lynch, Siewert J. Marrink, J. Andrew McCammon, Kenneth M. Merz, Adrian J. Mulholland, Athi N. Naganathan, Frank Noe, Agnes Noy, Megan L. O’Mara, Mary Jo Ondrechen, José N. Onuchic, Alberto Perez, Alberto Pérez, Juan Perilla, Jean-Philip Piquemal, Adolfo B. Poma, Matej Praprotnik, Nathalie Reuter, Carme Rovira, Benoît Roux, Ursula Rothlisberger, Karissa Y. Sanbonmatsu, Carlos Simmerling, Jeremy Smith, Yuji Sugita, Katarzyna Świderek, Peng Tao, D. Peter Tieleman, Irina G. Tikhonova, Julian Tirado-Rives, Sameer Velankar, Stacey D. Wetmore, Lee-Wei Yang, Martin Zacharias, Josep Ll. Gelpí, Ariel Warshel
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Nature
Verified
Challenges in bridging the gap between protein structure prediction and functional interpretation
CAD contact area difference CAID critical assessment of intrinsic disorder EM electron microscopy FAIR findable, accessible, interoperable, reusable GDT global distance test IDR intrinsically disordered region MSA multiple sequence alignments NMR nuclear magnetic resonance PAE predicted aligned error PDB protein data bank pLDDT predicted local distance difference test PPI protein–protein interaction 1 INTRODUCTION The advent of AI-based protein structure prediction tools, such as AlphaFold...
Clustering predicted structures at the scale of the known protein universe - Nature
Abstract Proteins are key to all cellular processes and their structure is important in understanding their function and evolution. Sequence-based predictions of protein structures have increased in accuracy1, and over 214 million predicted structures are available in the AlphaFold database2. However, studying protein structures at this scale requires highly efficient methods.
Structural biology: The transformational era
Structural biology has been undergoing an unprecedented transformation recently thanks to major breakthroughs in experimental methods such as cryogenic electron microscopy (cryo-EM) and ground-breaking computational approaches for predicting the 3D structure of proteins based on cutting edge deep-learning methods.
AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms - Communications Biology
Abstract Deep-learning (DL) methods like DeepMind’s AlphaFold2 (AF2) have led to substantial improvements in protein structure prediction. We analyse confident AF2 models from 21 model organisms using a new classification protocol (CATH-Assign) which exploits novel DL methods for structural comparison and classification. Of ~370,000 confident models, 92% can be assigned to 3253 superfamilies in our CATH domain superfamily classification. The remaining cluster into 2367 putative novel superfamilies.
A structural biology community assessment of AlphaFold2 applications - Nature Structural & Molecular Biology
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Abstract Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested.
By Arthur O. Zalevsky, Patrick Bryant, Lydia L. Good, Roman A. Laskowski, Gabriele Pozzati, Aditi Shenoy, Victoria Ruiz Serra, Alistair S. Dunham, David Burke, Sameer Velankar, Adam Frost, Kresten Lindorff-Larsen, Alex Bateman, Andrey V. Kajava, Alfonso Valencia, Sergey Ovchinnikov, Janani Durairaj, David Ascher, Janet Thornton, Norman E. Davey, Amelie Stein, Arne Elofsson, Tristan I. Croll
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Nature
Verified
Highly accurate protein structure prediction for the human proteome - Nature
Abstract Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure1.
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