Biomolecules Folding and Disease



Papers

Since 2004 we have published 73 peer-reviewed manuscripts (13 reviews) in international journal with impact factor and 7 book chapters. The complete list of research articles and book chapters is reported below.

2024

  1. Turina P, Dal Cortivo G, Enriquez Sandoval CA, Alexov E, Ascher DB, Babbi G, Bakolitsa C, Casadio R, Fariselli P, Folkman L, Kamandula A, Katsonis P, Li C, Lichtarge O, Martelli PL, Panday SK, Pires DEV, Portelli S, Pucci F, Rodrigues CHM, Rooman M, Savojardo C, Schwersensky M, Shen T, Strokach AV, Sun Y, Woo J, Radivojac P, Brenner SE, Dell'Orco D, Capriotti E. (2024). Assessing the predicted impact of single amino acid substitutions in calmodulin for CAGI6 challenges. Human Genetics. (Accepted)


  2. Abdelghani Attafi O, Clementel D, Kyritsis K, Capriotti E, Farrell G, Fragkouli SC, Castro LJ, Hatos A, Lenaerts T, Mazurenko S, Mozaffari S, Pradelli F, Ruch P, Savojardo C, Turina MP, Zambelli F, Piovesan D, Monzon AM, Psomopoulos F, Tosatto SCE. (2024). DOME Registry: Implementing community-wide recommendations for reporting supervised machine learning in biology. GigaScience. 13:giae094.


  3. Zhang J, Kinch L, Katsonis P, Lichtarge O, Jagota M, Song YS, Sun Y, Shen Y, Kuru N, Dereli O, Adebali O, Alladin MA, Pal D, Capriotti E, Turina MP, Savojardo C, Martelli PL, Babbi G, Casadio R, Hu Z, Pucci F, Rooman M, Cia G, Tsishyn M, Strokach A, van Loggerenberg W, Roth FP, Radivojac P, Brenner SE, Cong Q, Grishin NV. (2024). Assessing predictions on fitness effects of missense variants in HMBS in CAGI6. Human Genetics. DOI:10.1007/s00439-024-02680-3


  4. Critical Assessment of Genome Interpretation Consortium. (2024). CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods. Genome Biology. 17:95. DOI:10.1186/s40246-023-00544-x.


2023

  1. Petrosino M, Novak L, Pasquo A, Turina P, Capriotti E, Minicozzi V, Consalvi V, Chiaraluce R. (2023). The complex impact of cancer-related missense mutations on the stability and on the biophysical and biochemical properties of MAPK1 and MAPK3 somatic variants. Human Genomics. 17:95. DOI:10.1186/s40246-023-00544-x.
     

  2. Turina P, Fariselli P, Capriotti E*. (2023). K-Pro: Kinetics data on proteins and mutants. Journal of Molecular Biology. 435:168245. DOI:10.1016/j.jmb.2023.168245.
     

  3. Rocha J*, Sastre S, Amengual-Cladera E, Hernandez-Rodriguez J, Asensio-Landa V, Heine-Suner D, Capriotti E. (2023). Identification of driver epistatic gene pairs combining germline and somatic mutations in cancer. International Journal of Molecular Sciences. 24(11):9323. DOI: 10.3390/ijms24119323.
     

  4. Capriotti E*, Fariselli P*. (2023). PhD-SNPg: updating a webserver and lightweight tool for scoring nucleotide variants. Nucleic Acids Research. DOI:10.1093/nar/gkad455.
     

  5. Licata L, Via A, Turina P, Babbi G, Benevenuta S, Carta C, Casadio R, Cicconardi A, Facchiano A, Fariselli P, Giordano D, Isidori F, Marabotti A, Martelli PL, Pascarella S, Pinelli M, Pippucci T, Russo R, Savojardo C, Scafuri B, Valeriani L, Capriotti E* (2023). Resources and tools for rare disease variant interpretation. Frontiers in Molecular Biosciences. 10:1169109. DOI:10.3389/fmolb.2023.1169109.
     

  6. Benevenuta S, Birolo G, Sanavia T, Capriotti E, Fariselli P (2023). Challenges in predicting stabilizing variations: An exploration. Frontiers in Molecular Biosciences. 9:1075570. DOI:10.3389/fmolb.2022.1075570.
     

2022

  1. Montanucci L, Capriotti E, Birolo G, Benevenuta S, Pancotti C, Lal D, Fariselli P (2022). DDGun: an untrained predictor of protein stability changes upon amino acid variants. Nucleic Acids Research. DOI:10.1093/nar/gkac325.
     

  2. Capriotti E*, Fariselli P* (2022). Evaluating the relevance of sequence conservation in the prediction of pathogenic missense variants. Human Genetics.141:1649-1658. DOI:10.1007/s00439-021-02419-4.
     

  3. Pancotti C, Benevenuta S, Birolo G, Repetto V, Alberini V, Sanavia T, Capriotti E*, Fariselli P* (2022). Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset. Briefings in Bioinformatics. DOI:10.1093/bib/bbab555
     

2021

  1. Walsh I, Fishman D, Garcia-Gasulla D, Titma T, Pollastri G, Capriotti E , Casadio R, Capella-Gutierrez S, Cirillo D, Del Conte A, Dimopoulos AC, Del Angel V. D, Dopazo J, Fariselli P, Fernandez J. M, Huber F, Kreshuk A, Lenaerts T, Martelli PL, Navarro A, Broin PO, Pinero J, Piovesan D, Reczko M, Ronzano F, Satagopam V, Savojardo C, Spiwok V, Tangaro MA, Tartari G, Salgado D, Valencia A, Zambelli F, Harrow J, Psomopoulos FE, Tosatto SCE. (2021). DOME: recommendations for supervised machine learning validation in biology. Nature Methods. DOI:10.1038/s41592-021-01205-4.
     

  2. Merlotti A, Menichetti G, Fariselli P, Capriotti E, Remondini D. (2021). Network-based strategies for protein characterization. Advances in Protein Chemistry and Structural Biology. 127: 217-248. DOI:10.1016/bs.apcsb.2021.05.001.
     

  3. Pancotti C, Benevenuta S, Repetto V, Birolo G, Capriotti E, Sanavia T, Fariselli P. (2021). A deep-learning sequence-based method to predict protein stability changes upon genetic variations. Genes. 12:911. DOI:10.3390/genes12060911.
     

  4. Petrosino M, Novak L, Pasquo A, Chiaraluce R, Turina P, Capriotti E*, Consalvi V*. (2021). Analysis and interpretation of the impact of missense variants in cancer. International Journal of Molecular Sciences. 22:5416. DOI:10.3390/ijms22115416.
     

  5. Turina P, Fariselli P*, Capriotti E*. (2021). ThermoScan: Semi-automatic identification of protein stability data from PubMed. Frontiers in Molecular Biosciences.8:620475. DOI:10.3389/fmolb.2021.620475.
     

  6. Birolo G, Benevenuta S, Fariselli P*, Capriotti E*, Giorgio E, Sanavia T. (2021). Protein stability perturbation contributes to the loss of function in haploinsufficient genes. Frontiers in Molecular Biosciences. 8:620793. DOI:10.3389/fmolb.2021.620793.
     

  7. Benevenuta S, Capriotti E*, Fariselli P*. (2021). Calibrating variant-scoring methods for clinical decision making. Bioinformatics. 36:5709-5711.
     

2020

  1. Sanavia T, Birolo G, Montanucci L, Turina P, Capriotti E*, Fariselli P*. (2020). Limitations and challenges in protein stability prediction upon genome varia‐tions: towards future applications in precision medicine. Computational and Structural Biotechnology Journal. 18: 1968-1079.
     

2019

  1. Kasak L, Bakolitsa C, Hu Z, Yu C, Rine J, Dimster-Denk DF, Pandey G, De Baets G, Bromberg Y, Cao C, Capriotti E, Casadio R, Van Durme J, Giollo M, Karchin R, Katsonis P, Leonardi E, Lichtarge O, Martelli PL, Masica D, Mooney SD, Olatubosun A, Pal LR, Radivojac P, Rousseau F, Savojardo C, Schymkowitz J, Thusberg J, Tosatto SCE, Vihinen M, Väliaho J, Repo S, Moult J, Brenner SE, Friedberg I. (2019). Assessing Computational Predictions of the Phenotypic Effect of Cystathionine-beta-Synthase Variants. Human Mutation. 40: 1530-1545.
     

  2. Zhang J, Kinch LN, Cong Q, Katsonis P, Lichtarge O, Savojardo C, Babbi G, Martelli PL, Capriotti E, Casadio R, Garg A, Pal D, Weile J, Sun S, Verby M, Roth FP, Grishin NV. (2019) Assessing predictions on fitness effects of missense variants in calmodulin. Human Mutation. 40: 1463-1473.
     

  3. Monzon AM, Carraro M, Chiricosta L, Reggian F, Han J, Ozturk K, Wang Y, Miller M, Bromberg Y, Capriotti E, Savojardo C, Babbi G, Martelli PL, Casadio R, Katsonis P, Lichtarge O, Carter H, Kousi M, Katsanis N, Andreoletti G, Moult J, Brenner SE, Ferrari C, Leonardi E, Tosatto SCE. (2019). Performance of computational methods for the evaluation of Pericentriolar Material 1 missense variants in CAGI-5. Human Mutation. 40: 1474-1485.
     

  4. Voskanian A, Katsonis P, Lichtarge O, Pejaver V, Radivojac P, Mooney SD, Capriotti E, Bromberg Y, Wang Y, Miller M, Martelli PL, Savojardo C, Babbi G, Casadio R, Cao Y, Sun Y, Shen Y, Garg A, Pal D, Yu Y, Huff CD, Tavtigian SV, Young E, Neuhausen SL, Ziv E, Pal LR, Andreoletti G, Brenner S, Moult J, Kann MG. (2019). Assessing the performance of in-silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer. Human Mutation. 40: 1612-1622.
     

  5. Savojardo C, Petrosino M, Babbi G, Bovo S, Corbi-Verge C, Casadio R, Piero Fariselli P, Folkman L, Garg A, Karimi M, Katsonis P, Kim PM, Lichtarge O, Martelli PL, Pasquo A, Pal D, Shen Y, Strokach AV, Turina P, Zhou Y, Andreoletti G, Brenner S, Chiaraluce R, Consalvi V, Capriotti E*. (2019). Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge. Human Mutation. 40: 1392-1399.
     

  6. Montanucci L, Capriotti E*, Frank Y, Ben-Tal N, Fariselli P*. (2019). DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations. BMC Bioinformatics. 20 (Suppl 14): 335.
     

  7. McInnes G, Daneshjou R, Katsonis P, Lichtarge O, Srinivasan RG, Rana S, Radivojac P, Mooney SD, Pagel KA, Stamboulian M, Jiang Y, Capriotti E, Wang Y, Bromberg Y, Bovo S, Savojardo C, Martelli PL, Casadio R, Pal LR, Moult J, Brenner S, Altman R. (2019). Predicting venous thromboembolism risk from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges. Human Mutation. 40: 1314-1320.
     

  8. Petrosino M, Pasquo A, Novak L, Toto A, Gianni S, Mantuano E, Veneziano L, Minicozzi V, Pastore A, Puglisi R, Capriotti E, Chiaraluce R, Consalvi V. (2019). Characterization of human frataxin missense variants in cancer tissues. Human Mutation. 40: 1400-1413.
     

  9. Savojardo C, Babbi G, Bovo S, Capriotti E, Martelli PL, Casadio R. (2019). Are machine learning based methods suited to address complex biological problems? Lessons from CAGI‐5 challenges Human Mutation. 40: 1455-1462
     

  10. Capriotti E*, Montanucci L, Profiti G, Rossi I, Giannuzzi D, Aresu L, Fariselli P. (2019). Fido-SNP: The first webserver for scoring the impact of single nucleotide variants in the dog genome. Nucleic Acids Research. 47(W1): W136-W141.
     

  11. Capriotti E*, Ozturk K, Carter H*. (2019). Integrating molecular network with genetic variant interpretation for precision medicine. WIREs Systems Biology and Medicine. 11: e1443.
     

2017

  1. Capriotti E*, Fariselli P*. (2017). PhD-SNPg: A webserver and lightweight tool for scoring single nucleotide variants. Nucleic Acids Research. 45: W247-W252.
     

  2. Carraro M, Minervini G, Giollo M, Bromberg Y, Capriotti E, Casadio R, Dunbrack R, Elefanti L, Fariselli P, Ferrari C, Gough J, Katsonis P, Leonardi E, Lichtarge O, Menin C, Martelli PL, Niroula A, Pal LR, Repo S, Scaini MC, Vihinen M, Wei Q, Xu Q, Yang Y, Yin Y, Zaucha J, Zhao H, Zhou Y, Brenner SE, Moult J, Tosatto SCE. (2017). Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI. Human Mutation. 38: 1042-1050.
     

  3. Capriotti E*, Martelli PL, Fariselli P, Casadio R. (2017). Blind prediction of deleterious amino acid variations with SNPs&GO. Human Mutation. 38: 1064-1071.
     

2016

  1. Khass M, Blackburn T, Burrows PD, Walter MR, Capriotti E, Schroeder HW Jr. (2016). VpreB serves as an invariant surrogate antigen for selecting immunoglobulin antigen-binding sites. Science Immunology. 1: aaf6628.
     

2015

  1. Tian R, Basu MK, Capriotti E*. (2015). Computational methods and resources for the interpretation of genomic variants in cancer. BMC Genomics. 16 (Suppl. 8): S7.
     

  2. Beerten J, Van Durme J, Gallardo R, Capriotti E, Serpell L, Rousseau F, Schymkowitz J. (2015). WALTZ-DB: a benchmark database of amyloidogenic hexapeptides. Bioinformatics. 31:1698-1700.
     

2014

  1. Tian R, Basu MK, Capriotti E*. (2014). ContrastRank: a new method for ranking putative cancer driver genes and classification of tumor samples. Bioinformatics. 30: i572-i578.
     

  2. Di Tommaso P, Bussotti G, Kemena C, Capriotti E, Chatzou M, Prieto Barja P, Notredame C. (2014). SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments. Nucleic Acids Research. 42: W356-360
     

  3. Li B, Seligman C, Thusberg J, Miller JL, Auer J, Whirl-Carrillo M, Capriotti E, Klein TE, Mooney SD. (2014). In silico comparative characterization of pharmacogenomic missense variants. BMC Genomics. 15 (Suppl. 4): S4.
     

2013

  1. Compiani M*, Capriotti E*. (2013). Computational and theoretical methods for protein folding. Biochemistry. 52: 8601-8624.
     

  2. Norambuena T, Cares JF, Capriotti E, Melo F (2013). WebRASP: a server for computing energy scores to assess the accuracy and stability of RNA 3D structures. Bioinformatics. 29:2649-2650.
     

  3. Capriotti E*, Calabrese R, Fariselli P, Martelli PL, Altman RB, Casadio R* (2013). WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation. BMC Genomics. 14 Suppl 3:S6.
     

  4. Capriotti E*, Altman RB, Bromberg Y* (2013). Collective judgment predicts disease-associated single nucleotide variants. BMC Genomics. 14 Suppl 3:S2.
     

  5. Kemena C, Bussotti G, Capriotti E, Marti-Renom MA, Notredame C. (2013). Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package. Bioinformatics. 29:1112-1119.
     

2012

  1. Lahti JL, Tang GW, Capriotti E, Liu T, Altman RB. (2012). Bioinformatics and variability in drug response: a protein structural perspective. J R Soc Interface. 9; 1409-1437.
     

  2. Capriotti E*, Nehrt NL, Kann MG*, Bromberg Y*. (2012). Bioinformatics for personal genome interpretation. Briefings in Bioinformatics. 13; 495-512.
     

2011

  1. Dewey FE, Chen R, Cordero SP, Ormond KE, Caleshu C, Karczewski KJ, Whirl-Carrillo M, Wheeler MT, Dudley JT, Byrnes JK, Cornejo OE, Knowles JW, Woon M, Sangkuhl K, Gong L, Thorn CF, Hebert JM, Capriotti E, David SP, Pavlovic A, West A, Thakuria JV, Ball MP, Zaranek AW, Rehm HL, Church GM, West JS, Bustamante CD, Snyder M, Altman RB, Klein TE, Butte AJ, Ashley EA. (2011). Phased whole-genome genetic risk in a family quartet using a major allele reference sequence. PLOS Genetics. 7; e1002280.
     

  2. Capriotti E*, Altman RB. (2011). A new disease-specific machine learning approach for the prediction of cancer-causing missense variants. Genomics. 98; 310-317.
     

  3. Capriotti E*, Altman RB. (2011). Improving the prediction of disease-related variants using protein three-dimensional structure. BMC Bioinformatics. 12 (Suppl 4); S3
     

  4. Fernald GH, Capriotti E, Daneshjou R, Karczewski KJ, Altman RB. (2011). Bioinformatics challenges for personalized medicine. Bioinformatics. 27; 1741-1748
     

  5. Liu T, Tang GW, Capriotti E*. (2011). Comparative modeling: the state of the art and protein drug target structure prediction. Combinatorial Chemistry & High Throughput Screening. 14: 532-547
     

  6. Capriotti E, Norambuena T, Marti-Renom MA, Melo F. (2011). All atom knowledge-based potential for RNA structure prediction and assessment. Bioinformatics. 27; 1086-1093.
     

  7. Bau D, Sanyal A, Lajoie BR, Capriotti E, Byron M, Lawrence JB, Dekker J, Marti-Renom MA. (2011). The three-dimensional folding of the alpha-globin gene domain reveals formation of chromatin globules. Nat Struct Mol Biol. 18: 107-114.
     

2010

  1. Capriotti E, Marti-Renom MA. (2010). Quantifying the relationship between sequence and three-dimensional structure conservation in RNA. BMC Bioinformatics. 11: 322.
     

2009

  1. Calabrese R, Capriotti E, Fariselli P, Martelli PL, Casadio R. (2009). Functional annotations improve the predictive score of human disease-related mutations in proteins. Human Mutation. 30: 1237-1244.
     

  2. Capriotti E, Marti-Renom MA. (2009). SARA: a server for function annotation of RNA structures. Nucleic Acids Research. 37 (Web Server issue): W260-W265.
     

2008

  1. Capriotti E, Marti-Renom MA. (2008). RNA structure alignment by a unit-vector approach. Bioinformatics. 24: i112-i116.
     

  2. Capriotti E, Fariselli P, Rossi I, Casadio R. (2008). A three-state prediction of single point mutations on protein stability changes. BMC Bioinformatics. 9 (Suppl 2): S6.
     

  3. Capriotti E, Marti-Renom MA. (2008). Computational RNA structure prediction. Current Bioinformatics. 3: 32-45.
     

  4. Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. (2008). The use of estimated evolutionary strength at the codon level improves the prediction of disease related protein mutations in human. Human Mutation. 29: 198-204.
     

2007

  1. Capriotti E*, Casadio R. (2007). K-Fold: a tool for the prediction of the protein folding kinetic order and rate. Bioinformatics. 23: 385-386.
     

  2. Fariselli P, Rossi I, Capriotti E, Casadio R. (2007) The WWWH of remote homolog detection: The state of the art. Briefings in Bioinformatics. 8: 78-87.
     

2006

  1. Capriotti E, Compiani M. (2006). Diffusion-collision of foldons elucidates the kinetic effects of point mutations and suggests control strategies of the folding process of helical proteins. Proteins. 64: 198-209.
     

  2. Capriotti E, Calabrese R, Casadio R. (2006). Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics. 22: 2729-2734.
     

  3. Grandi F, Sandal M, Guarguaglini G, Capriotti E, Casadio R, Samori B. Hierarchical Mechanochemical Switches in Angiostatin. Chembiochem. 7: 1774-1782.
     

2005

  1. Stizza A, Capriotti E, Compiani M. (2005). A Minimal Model of Three-State Folding Dynamics of Helical Proteins. J. Phys. Chem. B. 109: 4215-4226.
     

  2. Capriotti E, Fariselli P, Casadio R. (2005). I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research. 33(Web Server issue): W306-W310.
     

  3. Capriotti E, Fariselli P, Calabrese R, Casadio R. (2005) Predicting protein stability changes from sequences using support vector machines. Bioinformatics. 21: ii54-ii58.
     

2004

  1. Capriotti E, Fariselli, Casadio R (2004). A neural network-based method for predicting protein stability changes upon single point mutations. Bioinformatics. 20 (Suppl 1): I63-I68
     

  2. Compiani M, Capriotti E, Casadio R. (2004). The Dynamics of the Minimally Frustrated Helices Determine the Hierarchical Folding of Small Helical Proteins. Physical Review E. 69: 051905
     

  3. Capriotti E, Fariselli P, Rossi I, Casadio R (2004). A Shannon entropy-based filter detects high-quality profile-profile alignments in searches for remote homologues. Proteins. 54: 351-360.
     


Book chapters

  1. Casadio R, Savojardo C, Fariselli P, Capriotti E, Martelli PL. (2022). Turning Failures into Applications: The Problem of Protein ΔΔG Prediction. Data Mining Techniques for the Life Sciences. Springer (Carugo O and Eisenhaber F Editors),169-185.
     

  2. Dufour D, Capriotti E, Marti-Renom MA. (2014). Computational methods for RNA structure prediction and analysis. RNA Nanotechnology. CRC Press (Wang B Editor), 21-50.
     

  3. Capriotti E. (2013). Comparative modeling and structure prediction: application to drug discovery. In silico drug discovery and design. Future Science (Lill MA Editor), 34-48.
     

  4. Marti-Renom MA, Capriotti E, Shindyalov I, Bourne P. (2009). Structural Comparison and Alignment. Structural Bioinformatics II Edition. John Wiley & Sons, Inc. (Gu J and Bourne PE Editors), 397-418.


  5. Capriotti E, Marti-Renom, MA. (2007). Assessment of protein structure predictions. Computational Structural Biology: Methods and Applications. World Scientific Publishing Company (Schwede T and Peitsch MC Editors), 89-109.
     

  6. Bartoli L, Capriotti E, Fariselli P, Martelli PL, Casadio R. (2007). The pros and cons of predicting protein contact maps. Protein Structure Prediction Series: Methods in Molecular Biology. Springer, Humana Press, (Zaki M and Bystroff C Editors) 2nd ed., 413: 199-218.
     

  7. Casadio R, Capriotti E, Compiani M, Fariselli P, Jacoboni I, Martelli PL Rossi I, Tasco G. (2003). Neural Networks and the Prediction of Protein Structure. In: Artificial Intelligence and Heuristic Methods for Bioinformatics (Frasconi P and Shamir R Editors) NATO Series Books. IOS Press Amsterdam, 22-33.


Citations