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ClinVar: public archive of interpretations of clinically relevant variants

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Protein-Protein Interactions

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BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations

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Molecular Mechanisms of Disease-Causing Missense Mutations

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Performance of protein stability predictors

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Calculation of the Relative Change in Binding Free Energy of a Protein-Inhibitor Complex

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SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models

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Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM

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Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins

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Molecular recognition of human angiogenin by placental ribonuclease inhibitor—an X‐ray crystallographic study at 2.0 Å resolution

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On Human Disease-Causing Amino Acid Variants: Statistical Study of Sequence and Structural Patterns

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Analyzing Effects of Naturally Occurring Missense Mutations

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Modeling Effects of Human Single Nucleotide Polymorphisms on Protein-Protein Interactions

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Cancer Missense Mutations Alter Binding Properties of Proteins and Their Interaction Networks

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Predicting the Impact of Missense Mutations on Protein–Protein Binding Affinity

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Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method

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A missense mutation in CLIC2 associated with intellectual disability is predicted by in silico modeling to affect protein stability and dynamics

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An X-linked channelopathy with cardiomegaly due to a CLIC2 mutation enhancing ryanodine receptor channel activity

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Scoring functions for protein–protein interactions

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Computational analysis of missense mutations causing Snyder-Robinson syndrome

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Approaches and Resources for Prediction of the Effects of Non-Synonymous Single Nucleotide Polymorphism on Protein Function and Interactions

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In Silico and In Vitro Investigations of the Mutability of Disease-Causing Missense Mutation Sites in Spermine Synthase

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Investigating the linkage between disease-causing amino acid variants and their effect on protein stability and binding

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The structure of human liver fructose-1,6-bisphosphate aldolase

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Proteome-wide prediction of protein-protein interactions from high-throughput data

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Mutations in the promoter region of the aldolase B gene that cause hereditary fructose intolerance

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Mapping proteome-wide interactions of reactive chemicals using chemoproteomic platforms

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Computational and Experimental Approaches to Reveal the Effects of Single Nucleotide Polymorphisms with Respect to Disease Diagnostics

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Hereditary fructose intolerance: Frequency and spectrum mutations of the aldolase B gene in a large patients cohort from France—Identification of eight new mutations

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Identification of a novel missense mutation in angiogenin in a Chinese amyotrophic lateral sclerosis cohort

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Aldolase B mutations and prevalence of hereditary fructose intolerance in a Polish population

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Mutations in the KDM5C ARID Domain and Their Plausible Association with Syndromic Claes-Jensen-Type Disease

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Understanding Molecular Effects of Naturally Occurring Genetic Differences

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Chronic Beryllium Disease: Revealing the Role of Beryllium Ion and Small Peptides Binding to HLA-DP2

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Protein-Protein Interactions: Structures and Druggability

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Association between the Angiogenin (ANG) K17I variant and amyotrophic lateral sclerosis risk in Caucasian: a meta-analysis

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Editorial [ Protein-Protein Interactions Guest Editor: Emil Alexov ]

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Physics approaches to protein interactions and gene regulation

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Immunohistochemical studies of angiogenin in the skin of patients with amyotrophic lateral sclerosis

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Editorial overview: Linking protein sequence and structural changes to function in the era of next-generation sequencing

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Recent Developments and Applications of the MMPBSA Method

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Mutations Strengthened SARS-CoV-2 Infectivity

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mCSM-PPI2: predicting the effects of mutations on protein–protein interactions

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A topology-based network tree for the prediction of protein–protein binding affinity changes following mutation

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MutaBind2: predicting the impacts of single and multiple mutations on protein-protein interactions

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Deep geometric representations for modeling effects of mutations on protein-protein binding affinity

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Protein–protein interactions: scoring schemes and binding affinity

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Computational Alanine Scanning with Interaction Entropy for Protein–Ligand Binding Free Energies

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SAAMBE-3D: Predicting Effect of Mutations on Protein–Protein Interactions

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Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?

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Directed Evolution of l -Threonine Aldolase for the Diastereoselective Synthesis of β-Hydroxy-α-amino Acids

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Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

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PROXiMATE: a database of mutant protein–protein complex thermodynamics and kinetics

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Persistent Laplacian projected Omicron BA.4 and BA.5 to become new dominating variants

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DelPhi Suite: New Developments and Review of Functionalities

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Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework

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Pretrainable geometric graph neural network for antibody affinity maturation

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Construction of a Highly Diastereoselective Aldol Reaction System with l -Threonine Aldolase by Computer-Assisted Rational Molecular Modification and Medium Engineering

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Persistent spectral based ensemble learning (PerSpect-EL) for protein–protein binding affinity prediction

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Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

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PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions

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SAAMBE-SEQ: a sequence-based method for predicting mutation effect on protein–protein binding affinity

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Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows

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Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases

Peng, Y., Alexov, E., & Basu, S. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20030548 · Cited by 40 · see citing works

Computational Approaches to Prioritize Cancer Driver Missense Mutations

Zhao, F., Zheng, L., Goncearenco, A., Panchenko, A. R., & Li, M. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19072113 · Cited by 33 · see citing works

RheoScale: A tool to aggregate and quantify experimentally determined substitution outcomes for multiple variants at individual protein positions

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Reproducing the Ensemble Average Polar Solvation Energy of a Protein from a Single Structure: Gaussian-Based Smooth Dielectric Function for Macromolecular Modeling

Chakravorty, A., Jia, Z., Li, L., Zhao, S., & Alexov, E. G. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00756 · Cited by 26 · see citing works

Three additional patients with EED-associated overgrowth: potential mutation hotspots identified?

Spellicy, C. J., Peng, Y., Olewiler, L., Cathey, S. S., Rogers, R. C., Bartholomew, D., Johnson, J., Alexov, E. G., Lee, J. A., Friez, M. J., et al. (2019) · Journal of Human Genetics · doi:10.1038/s10038-019-0585-5 · Cited by 22 · see citing works

PremPRI: Predicting the Effects of Missense Mutations on Protein–RNA Interactions

Zhang, N., Lu, H., Chen, Y., Zhu, Z., Yang, Q., Wang, S., & Li, M. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21155560 · Cited by 22 · see citing works

Using collections of structural models to predict changes of binding affinity caused by mutations in protein–protein interactions

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DGCddG: Deep Graph Convolution for Predicting Protein-Protein Binding Affinity Changes Upon Mutations

Jiang, Y., Quan, L., Li, K., Li, Y., Zhou, Y., Wu, T., & Lyu, Q. (2023) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3233627 · Cited by 20 · see citing works

DMAKit: A user-friendly web platform for bringing state-of-the-art data analysis techniques to non-specific users

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Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

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Hom-Complex-Based Machine Learning (HCML) for the Prediction of Protein–Protein Binding Affinity Changes upon Mutation

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Predicting the Effect of Single Mutations on Protein Stability and Binding with Respect to Types of Mutations

Pandey, P., Panday, S. K., Rimal, P., Ancona, N., & Alexov, E. G. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241512073 · Cited by 19 · see citing works

ProBASS—a language model with sequence and structural features for predicting the effect of mutations on binding affinity

Gurusinghe, S. N. S., Wu, Y., DeGrado, W. F., & Shifman, J. M. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf270 · Cited by 15 · see citing works

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors

Lin, Y.-J., Menon, A. S., Hu, Z., & Brenner, S. E. (2024) · Human Genomics · doi:10.1186/s40246-024-00663-z · Cited by 14 · see citing works

Generating quantitative binding landscapes through fractional binding selections combined with deep sequencing and data normalization

Heyne, M., Papo, N., & Shifman, J. M. (2020) · Nature Communications · doi:10.1038/s41467-019-13895-8 · Cited by 15 · see citing works

Computational analysis for residue-specific CDK2-inhibitor bindings

Yang, Y.-P., He, L., Bao, J.-X., Qi, Y.-F., & Zhang, J. Z. H. (2019) · Chinese Journal of Chemical Physics · doi:10.1063/1674-0068/cjcp1901012 · Cited by 12 · see citing works

Comprehensive screening strategy coupled with structure-guided engineering of l-threonine aldolase from Pseudomonas putida for enhanced catalytic efficiency towards l-threo-4-methylsulfonylphenylserine

Li, L., Zhang, R., Xu, Y., & Zhang, W. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1117890 · Cited by 11 · see citing works

Computational analyses prioritize and reveal the deleterious nsSNPs in human angiotensinogen gene

Goswami, A. M. (2020) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2019.107199 · Cited by 11 · see citing works

Persistent Tor-algebra for protein–protein interaction analysis

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Cofactors-loaded quaternary structure of lysine-specific demethylase 5C (KDM5C) protein: Computational model

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Mutantelec: An In Silico mutation simulation platform for comparative electrostatic potential profiling of proteins

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Biomolecular Topology: Modelling and Analysis

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Rationally introducing non-canonical amino acids to enhance catalytic activity of LmrR for Henry reaction

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Probing the Immune System Dynamics of the COVID-19 Disease for Vaccine Designing and Drug Repurposing Using Bioinformatics Tools

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Human IgG1 Fc pH-dependent optimization from a constant pH molecular dynamics simulation analysis

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In-silico analysis to identify the role of MEN1 missense mutations in breast cancer

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Contribution of allosteric disulfide in the structural regulation of membrane-bound tissue factor–factor VIIa binary complex

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Novel Genetic Markers for Early Detection of Elevated Breast Cancer Risk in Women

Wu, B., Peng, Y., Eggert, J. A., & Alexov, E. G. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20194828 · Cited by 5 · see citing works

VariBench, new variation benchmark categories and data sets

Shirvanizadeh, N., & Vihinen, M. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1248732 · Cited by 4 · see citing works

Integrated engineering at distal site and active center regulates stereoselectivity and activity of carbonyl reductase towards N-Boc-pyrrolidone

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Categorization of hotspots into three types – weak, moderate and strong to distinguish protein–protein versus protein–peptide interactions

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A grid‐based algorithm in conjunction with a gaussian‐based model of atoms for describing molecular geometry

Chakravorty, A., Gallicchio, E., & Alexov, E. G. (2019) · Journal of Computational Chemistry · doi:10.1002/jcc.25786 · Cited by 3 · see citing works

Computational analysis of hereditary spastic paraplegia mutations in the kinesin motor domains of KIF1A and KIF5A

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Machine learning detection of SARS-CoV-2 high-risk variantsPreprint

Li, L., Li, C., Li, N., Zou, D., Zhao, W., Xue, Y., Zhang, Z., Bào, Y., & Song, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.19.537460 · Cited by 3 · see citing works

MM-PBSA: Challenges and opportunities

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Integrating Computational Approaches to Predict the Effect of Genetic Variants on Protein Stability in Retinal Degenerative Disease

Grunin, M. A., Palmer, E. L., de Jong, S., Jin, B., Rinker, D. C., Moth, C. W., Capra, J. A., Haines, J. L., Bush, W. S., & den Hollander, A. I. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-27681-1_24 · Cited by 2 · see citing works

Beyond gene expression

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In silico design of ACE2 mutants for competitive binding of SARS-CoV-2 receptor binding domain with hACE2

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Three types of hotspots- weak, moderate and strong in protein-protein and protein-peptide interactionsPreprint

Kumar, A. K., & Rathore, R. S. (2022) · doi:10.22541/au.167101052.24746048/v1

Geometric and topological AI for molecular sciences

Wee, J. (2023) · doi:10.32657/10356/165903

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictorsPreprint

Lin, Y.-J., Menon, A. S., Hu, Z., & Brenner, S. E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.25.600283

Additional file 1 of Rationally introducing non-canonical amino acids to enhance catalytic activity of LmrR for Henry reaction

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FAIRsharing record for: PROtein-protein compleX MutAtion ThErmodynamics Database

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SAMBE: The New Webserver for Predicting the Effect of nssNP on the Protein-Protein Binding Free Energy

Petukh, M. G., Morrison, J., Li, M., Panchenko, A. R., & Alexov, E. G. (2015) · Biophysical Journal · doi:10.1016/j.bpj.2014.11.867

RESEARCH ARTICLE Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge- Modified MM/PBSA Method

Petukh, M. G., Li, M., & Alexov, E. G. (2016)

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method

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SAAMBE-SEQ: a sequence-based method for predicting mutation effect on protein–protein binding affinity

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SAAMBE-3D: Predicting Effect of Mutations on Protein–Protein Interactions

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