World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
38
Citations
6172
World Ranking
8015
National Ranking
2211

Research.com Recognitions

  • 2010 - National Institutes of Health Director's Pioneer Award

Overview

Ram Samudrala is affiliated with the University at Buffalo, State University of New York in the United States. Their research spans various domains within biochemistry, genetics, and molecular biology, with significant contributions to medicine as well.

The main fields of study of Ram Samudrala encompass:

  • Biochemistry, Genetics and Molecular Biology
  • Medicine

Within these fields, they have focused on several subfields, including:

  • Molecular Biology
  • Computational Theory and Mathematics
  • Pharmacology
  • Infectious Diseases
  • Pulmonary and Respiratory Medicine

The primary research topics covered by Ram Samudrala include:

  • Computational Drug Discovery Methods
  • Bioinformatics and Genomic Networks
  • Microbial Natural Products and Biosynthesis
  • Vaccines and Immunoinformatics Approaches
  • RNA Research and Splicing
  • RNA Modifications and Cancer
  • Pharmacogenetics and Drug Metabolism

Notable recent scientific papers by Ram Samudrala involve collaborations on the following works:

  • "Antiviral Approaches against Influenza Virus," 2023, Clinical Microbiology Reviews
  • "Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function," 2021, Nature Communications
  • "CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials," 2020, Journal of Chemical Information and Modeling
  • "Evaluating the performance of drug-repurposing technologies," 2021, Drug Discovery Today
  • "A synthetic small molecule stalls pre-mRNA splicing by promoting an early-stage U2AF2-RNA complex," 2021, Cell Chemical Biology

Ram Samudrala frequently collaborates with several co-authors, among whom the most frequent include:

  • Zackary Falls
  • William Mangione
  • Liana Bruggemann
  • Matthew L. Hudson
  • Melissa Van Norden

The scientist's research outputs have been published in a range of venues, most notably:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Faculty Opinions - Post-Publication Peer Review of the Biomedical Literature
  • Journal of Chemical Information and Modeling
  • Drug Discovery Today
  • Molecules

In recognition of their contributions, Ram Samudrala was awarded the National Institutes of Health Director's Pioneer Award in 2010.

Best Publications

  • An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction.

    Ram Samudrala;John Moult

  • Data access for the 1,000 Plants (1KP) project.

    Naim Matasci;Ling Hong Hung;Zhixiang Yan;Eric J. Carpenter

  • Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

    Ram Samudrala;Fred Heffron;Jason E. McDermott

  • Ab initio construction of protein tertiary structures using a hierarchical approach.

    Yu Xia;Enoch S. Huang;Michael Levitt;Ram Samudrala

  • A GRAPH-THEORETIC ALGORITHM FOR COMPARATIVE MODELING OF PROTEIN STRUCTURE

    Ram Samudrala;Ram Samudrala;John Moult

  • A novel knowledge-based approach to design inorganic-binding peptides

    Ersin Emre Oren;Candan Tamerler;Deniz Sahin;Marketa Hnilova

  • Mouse transcriptome: neutral evolution of 'non-coding' complementary DNAs.

    Jun Wang;Jianguo Zhang;Hongkun Zheng;Jun Li

  • Novel paradigms for drug discovery: computational multitarget screening

    Ekachai Jenwitheesuk;Ekachai Jenwitheesuk;Jeremy A. Horst;Kasey L. Rivas;Wesley C. Van Voorhis

  • Ab initio protein structure prediction using a combined hierarchical approach.

    Ram Samudrala;Yu Xia;Enoch Huang;Michael Levitt

  • Caries induced cytokine network in the odontoblast layer of human teeth

    Orapin V Horst;Orapin V Horst;Jeremy A Horst;Jeremy A Horst;Ram Samudrala;Beverly A Dale

  • Computational prediction of type III and IV secreted effectors in gram-negative bacteria.

    Jason E. McDermott;Abigail L. Corrigan;Elena S. Peterson;Christopher S. Oehmen

  • Structural polymorphism and diversifying selection on the pregnancy malaria vaccine candidate VAR2CSA.

    Joseph Bockhorst;Fangli Lu;Joel H. Janes;Jon Keebler

  • Incorporating background frequency improves entropy-based residue conservation measures

    Kai Wang;Ram Samudrala

  • Structural optimization and de novo design of dengue virus entry inhibitory peptides.

    Joshua M. Costin;Ekachai Jenwitheesuk;Shee Mei Lok;Elizabeth Hunsperger

  • Ab initio fold prediction of small helical proteins using distance geometry and knowledge-based scoring functions.

    Enoch S. Huang;Ram Samudrala;Jay W. Ponder

  • Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function

    L. Palanikumar;Laura Karpauskaite;Mohamed Al-Sayegh;Ibrahim Chehade

  • Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design

    Gong Cheng;Bin Qian;Ram Samudrala;David Baker

  • Improved prediction of HIV-1 protease-inhibitor binding energies by molecular dynamics simulations.

    Ekachai Jenwitheesuk;Ekachai Jenwitheesuk;Ram Samudrala

  • Probing the molecular mechanisms of quartz-binding peptides.

    Ersin Emre Oren;Rebecca Notman;Il Won Kim;John Spencer Evans

  • A combined approach for ab initio construction of low resolution protein tertiary structures from sequence.

    Ram Samudrala;Yu Xia;Michael Levitt;Enoch S Huang

  • Improved protein structure selection using decoy-dependent discriminatory functions

    Kai Wang;Boris Fain;Michael Levitt;Ram Samudrala

  • PROTINFO: new algorithms for enhanced protein structure predictions.

    Ling-Hong Hung;Shing-Chung Ngan;Tianyun Liu;Ram Samudrala

  • CANDO and the infinite drug discovery frontier

    Mark Minie;Gaurav Chopra;Geetika Sethi;Jeremy Horst

Frequent Co-Authors

Gane Ka-Shu Wong
Gane Ka-Shu Wong University of Alberta
Candan Tamerler
Candan Tamerler University of Kansas
Kai Wang
Kai Wang Hebei University
Michael Levitt
Michael Levitt Stanford University
Mehmet Sarikaya
Mehmet Sarikaya University of Washington
Jun Yu
Jun Yu Chinese University of Hong Kong
huanming yang
huanming yang Beijing Genomics Institute
Siqi Liu
Siqi Liu Chinese Academy of Sciences
John Moult
John Moult University of Maryland, College Park
Heng Li
Heng Li Harvard University

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